{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.metrics import roc_auc_score\n",
    "from sklearn.datasets import make_classification\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from lightgbm import LGBMClassifier\n",
    "from shaphypetune import BoostSearch, BoostBoruta, BoostRFE\n",
    "\n",
    "import warnings\n",
    "warnings.simplefilter('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def binary_performances(y_true, y_prob, thresh=0.5, labels=['Positives','Negatives']):\n",
    "    \n",
    "    import seaborn as sns\n",
    "    import matplotlib.pyplot as plt\n",
    "    from sklearn.metrics import confusion_matrix, auc, roc_curve\n",
    "    \n",
    "    shape = y_prob.shape\n",
    "    if len(shape) > 1:\n",
    "        if shape[1] > 2:\n",
    "            raise ValueError('A binary class problem is required')\n",
    "        else:\n",
    "            y_prob = y_prob[:,1]\n",
    "    \n",
    "    plt.figure(figsize=[15,4])\n",
    "    \n",
    "    #1 -- Confusion matrix\n",
    "    cm = confusion_matrix(y_true, (y_prob>thresh).astype(int))\n",
    "    \n",
    "    plt.subplot(131)\n",
    "    ax = sns.heatmap(cm, annot=True, cmap='Blues', cbar=False, \n",
    "                     annot_kws={\"size\": 14}, fmt='g')\n",
    "    cmlabels = ['True Negatives', 'False Positives',\n",
    "               'False Negatives', 'True Positives']\n",
    "    for i,t in enumerate(ax.texts):\n",
    "        t.set_text(t.get_text() + \"\\n\" + cmlabels[i])\n",
    "    plt.title('Confusion Matrix', size=15)\n",
    "    plt.xlabel('Predicted Values', size=13)\n",
    "    plt.ylabel('True Values', size=13)\n",
    "      \n",
    "    #2 -- Distributions of Predicted Probabilities of both classes\n",
    "    plt.subplot(132)\n",
    "    plt.hist(y_prob[y_true==1], density=True, bins=25,\n",
    "             alpha=.5, color='green',  label=labels[0])\n",
    "    plt.hist(y_prob[y_true==0], density=True, bins=25,\n",
    "             alpha=.5, color='red', label=labels[1])\n",
    "    plt.axvline(thresh, color='blue', linestyle='--', label='Boundary')\n",
    "    plt.xlim([0,1])\n",
    "    plt.title('Distributions of Predictions', size=15)\n",
    "    plt.xlabel('Positive Probability (predicted)', size=13)\n",
    "    plt.ylabel('Samples (normalized scale)', size=13)\n",
    "    plt.legend(loc=\"upper right\")\n",
    "    \n",
    "    #3 -- ROC curve with annotated decision point\n",
    "    fp_rates, tp_rates, _ = roc_curve(y_true, y_prob)\n",
    "    roc_auc = auc(fp_rates, tp_rates)\n",
    "    plt.subplot(133)\n",
    "    plt.plot(fp_rates, tp_rates, color='orange',\n",
    "             lw=1, label='ROC curve (area = %0.3f)' % roc_auc)\n",
    "    plt.plot([0, 1], [0, 1], lw=1, linestyle='--', color='grey')\n",
    "    tn, fp, fn, tp = [i for i in cm.ravel()]\n",
    "    plt.plot(fp/(fp+tn), tp/(tp+fn), 'bo', markersize=8, label='Decision Point')\n",
    "    plt.xlim([0.0, 1.0])\n",
    "    plt.ylim([0.0, 1.05])\n",
    "    plt.xlabel('False Positive Rate', size=13)\n",
    "    plt.ylabel('True Positive Rate', size=13)\n",
    "    plt.title('ROC Curve', size=15)\n",
    "    plt.legend(loc=\"lower right\")\n",
    "    plt.subplots_adjust(wspace=.3)\n",
    "    plt.show()\n",
    "\n",
    "    tn, fp, fn, tp = [i for i in cm.ravel()]\n",
    "    precision = tp / (tp + fp)\n",
    "    recall = tp / (tp + fn)\n",
    "    F1 = 2*(precision * recall) / (precision + recall)\n",
    "    results = {\n",
    "        \"Precision\": precision, \"Recall\": recall,\n",
    "        \"F1 Score\": F1, \"AUC\": roc_auc\n",
    "    }\n",
    "    \n",
    "    prints = [f\"{kpi}: {round(score, 3)}\" for kpi,score in results.items()]\n",
    "    prints = ' | '.join(prints)\n",
    "    print(prints)\n",
    "    \n",
    "    return results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((150000, 50), (150000,))"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### CREATE SYNTHETIC DATA ### \n",
    "\n",
    "X, y = make_classification(n_samples=150_000, \n",
    "                           n_features=50, n_informative=11, n_redundant=10,\n",
    "                           n_classes=2, weights=[0.9, 0.1], class_sep=0.5, \n",
    "                           random_state=33, shuffle=True)\n",
    "\n",
    "X = pd.DataFrame(X, columns=[f\"feat_{c}\" for c in range(X.shape[1])])\n",
    "X.shape, y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "### CREATE CATEGORICAL COLUMNS ###\n",
    "\n",
    "cat_col = [f\"feat_{c}\" for c in range(10)]\n",
    "X[cat_col] = X[cat_col].round(2).astype(\"category\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "### TRAIN TEST SPLIT ###\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X, y, test_size=0.3, shuffle=True, random_state=33)\n",
    "\n",
    "X_train, X_valid, y_train, y_valid = train_test_split(\n",
    "    X_train, y_train, test_size=0.2, shuffle=True, random_state=33)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "### DEFINE TUNING VARIABLES ###\n",
    "\n",
    "param_grid = {\n",
    "    'n_estimators': 200,\n",
    "    'learning_rate': [0.3, 0.2, 0.1],\n",
    "    'num_leaves': [20, 25, 30, 35]\n",
    "}\n",
    "\n",
    "def AUC(y_true, y_hat):\n",
    "    return 'auc', roc_auc_score(y_true, y_hat), True\n",
    "\n",
    "results = {}\n",
    "\n",
    "lgbm = LGBMClassifier(random_state=0, n_jobs=-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "12 trials detected for ('n_estimators', 'learning_rate', 'num_leaves')\n",
      "\n",
      "trial: 0001 ### iterations: 00010 ### eval_score: 0.87987\n",
      "trial: 0002 ### iterations: 00008 ### eval_score: 0.88682\n",
      "trial: 0003 ### iterations: 00010 ### eval_score: 0.884\n",
      "trial: 0004 ### iterations: 00007 ### eval_score: 0.87937\n",
      "trial: 0005 ### iterations: 00025 ### eval_score: 0.90459\n",
      "trial: 0006 ### iterations: 00016 ### eval_score: 0.8999\n",
      "trial: 0007 ### iterations: 00018 ### eval_score: 0.89381\n",
      "trial: 0008 ### iterations: 00021 ### eval_score: 0.90012\n",
      "trial: 0009 ### iterations: 00009 ### eval_score: 0.89066\n",
      "trial: 0010 ### iterations: 00014 ### eval_score: 0.89568\n",
      "trial: 0011 ### iterations: 00013 ### eval_score: 0.88415\n",
      "trial: 0012 ### iterations: 00010 ### eval_score: 0.88876\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "BoostSearch(estimator=LGBMClassifier(random_state=0), greater_is_better=True,\n",
       "            param_grid={'learning_rate': [0.3, 0.2, 0.1], 'n_estimators': 200,\n",
       "                        'num_leaves': [20, 25, 30, 35]})"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### HYPERPARAM TUNING WITH GRID-SEARCH ###\n",
    "\n",
    "model = BoostSearch(lgbm, param_grid=param_grid, greater_is_better=True)\n",
    "model.fit(X_train, y_train, eval_set=[(X_valid, y_valid)], eval_metric=AUC, early_stopping_rounds=3, verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Precision: 0.906 | Recall: 0.311 | F1 Score: 0.463 | AUC: 0.905\n"
     ]
    }
   ],
   "source": [
    "### PLOT AND STORE RESULTS ###\n",
    "\n",
    "results['Param Tuning'] = binary_performances(y_test, model.predict_proba(X_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "12 trials detected for ('n_estimators', 'learning_rate', 'num_leaves')\n",
      "\n",
      "trial: 0001 ### iterations: 00010 ### eval_score: 0.87987\n",
      "trial: 0002 ### iterations: 00008 ### eval_score: 0.88682\n",
      "trial: 0003 ### iterations: 00014 ### eval_score: 0.88941\n",
      "trial: 0004 ### iterations: 00012 ### eval_score: 0.88275\n",
      "trial: 0005 ### iterations: 00025 ### eval_score: 0.90459\n",
      "trial: 0006 ### iterations: 00022 ### eval_score: 0.90515\n",
      "trial: 0007 ### iterations: 00027 ### eval_score: 0.90146\n",
      "trial: 0008 ### iterations: 00025 ### eval_score: 0.90454\n",
      "trial: 0009 ### iterations: 00020 ### eval_score: 0.89959\n",
      "trial: 0010 ### iterations: 00014 ### eval_score: 0.89568\n",
      "trial: 0011 ### iterations: 00020 ### eval_score: 0.89687\n",
      "trial: 0012 ### iterations: 00015 ### eval_score: 0.89909\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "BoostRFE(estimator=LGBMClassifier(random_state=0), greater_is_better=True,\n",
       "         min_features_to_select=10,\n",
       "         param_grid={'learning_rate': [0.3, 0.2, 0.1], 'n_estimators': 200,\n",
       "                     'num_leaves': [20, 25, 30, 35]},\n",
       "         step=3)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### HYPERPARAM TUNING WITH GRID-SEARCH + RECURSIVE FEATURE ELIMINATION (RFE) ###\n",
    "\n",
    "model = BoostRFE(lgbm, param_grid=param_grid, min_features_to_select=10, step=3, greater_is_better=True)\n",
    "model.fit(X_train, y_train, eval_set=[(X_valid, y_valid)], eval_metric=AUC, early_stopping_rounds=3, verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ishG7LtcYbG/s09iFcBOs5ZRGFgOPisgO4G9sdMvCrgIissGR24nt7XkA2yuVIIKlw1xsg7dSRF7ARpKagJ30Ozud9I7FGBOE7XFKKj9U7FILL4jIeayP+Risy4HrtcYscD1SRNYB5x13uVThvNR+DAQaY75y0mYDM0VkfSa+HCrZHy8RiYnQWQgbgvth7AtvZ5PEem0i8iDWsFqFDShUBWusfAJgjLkqIv9glzrZie3p/T0N+p0CPhWR/2ENkUlYQ2+uU0+0iCwFnnTm0Z7DRuqNv7bTbqCU2CVTdmID2BxMpL43nOtfLSKvYl26p2DnMH6dWqVFpAiwGvt97MV2CD2F7a3+K7FzjDFnROQtYJyIRGLdDXtgFzrul9g5GYEx5pzYpRPednrV12M736oC7Ywx3R3RycAisetxLcZG8+ucSJGuZUeLXfphgYgswK4PZrAdgJ87nhFZ/rdSFHdjjDEiMhl7L91mjPneGHNZ7BJRK4AgEZmOdZdsgI2G/hvwP5cyQpz77HMRKY+divIvNlBKH+w9ndwoYH+s2/c2EXmTa4uzd8K+vzUBjmDbh2GOzAqsJ0lqvNBcCcROAXoSG+wl1pAzxuwRkVnAQhF5Ddt2+gC1gKrGmPuvsy4lrbg7koxuBuBe7I0Ziu1F3Yvt2XGN2FYC+9A7i31h+hFoFK+cg7hE13PSBhMvkhyJR+osiF2K4Az2YTqOhNE4p2If2BewL28/AK1c8uPIO2k3Y+cBXsAatN8AVeLJpBg5NInvLTUycaJ3YqNIrcMaq4ex653Fv07BhhAPwRqGQcnVR8IoV7OxvXm+8b7fv4Gv3f1/0y17bFyLFmuc/+E57MPyZde2wZGtRNzonc2wD+8QrEH3D3Z00DWSXEesoXfFObdS/HLi1RGnfcGJ1og1fPZiR9A34hLF1pErhe3QOo9deHw4CSM9+mA7Sk449c91rSNeefWce/iy8518hp0Ll+h3EV9f53Ne7DzbPU45p7BtU50UfhNP7CjTEWxbvQvoH09mMNcXvTNJORKJqueSdx+2Jz8M+1zYAoyKJzMC24t/GTu3syPJRO90SevhlH0F28m4AqiYnX4r3XTLrI2k3w08sW3j6njptYEvsG7Y4Y7MJKBAEuXXc+T/w478hWBHEuunQrfSwNvY949wp61YjQ0y4yo31mnXLjhldyPx6J0Jng1OvmDfqQzQKYn8J7Cjn+HOtf8IDHT375ebNnF+DEVRFEVRFEVRFCUHonP6FEVRFEVRFEVRcjBq9CmKoiiKoiiKouRg1OhTFEVRFEVRFEXJwajRpyiKoiiKoiiKkoPJFks25Ks3QqPN5CDObp3hbhWUdMbHC3G3DlkNPz8/U6lSJXeroaQTe5xFW6pVc68eSvqxffv2U8aYEu7WI6uhbZeiZF1upN3KFkafoihKdqNSpUps27bN3Woo6UTbtnYfFOROLZT0xFk7UomHtl2KknW5kXZL3TsVRVEURVEURVFyMDrSpyiKoigpMG6cuzVQFEVRlLSjRp+iKIqipECHDu7WQFEURVHSjhp9iqIoipICwcF2HxCQsfVERERw9OhRrly5krEV5SJ8fHwoX7483t7e7lZFURTFbajRpyiKoigp8MQTdp/RgVyOHj1KoUKFqFSpEiIaFPdGMcZw+vRpjh49SuXKld2tjqIoitvQQC6KoiiKkkW4cuUKvr6+avClEyKCr6+vjpwqipLrUaNPURRFUbIQavClLzn1+xSROSJyQkR2JpEvIjJdRPaLyO8iUj+zdVQUJeugRp+iKIqiKEr2Yy7QOZn8LkAVZxsOzMwEnRRFyaLonD5FURRFUWLx9PSkTp06GGPw9PRkxowZNG/ePEPrjFkQ3M/PL0PryUkYY9aLSKVkRO4GPjHGGGCziBQVkTLGmGOZoqCi5EaMgagrEHHebiYq8e3qWQgLgagwexwd6eRF2vOvHIfLRyE6wqZFR3IotOANqaZGn6IoSmYyYULa8hS3MnmyuzXIPPLly0ewE6509erVjB07lh9//NHNWsUlKioKT09Pd6uR1SkHHHE5PuqkJTD6RGQ4djSQm266KVOUU5QsRXQURF60hlr0VbuFn4JLB63xFXnJHkdcgOhwCDtm9+Gn4eoZ8PSBqHCICLXleXiDZwHwKQnimXCLDocClSB/ORAvm+YRs88LRepAmS7gmQ88vNn0RwibDx4FVqb5EtXoUxQlVyAic4A7gRPGmNpOWiBQzREpCpwzxiQIyi8iB4ELQBQQaYxpmClKK1mGDB7oyrKcP3+eYsWKATYS5jPPPMPKlSsREcaNG0efPn0ICgpi2rRpfPPNNwCMGDGChg0bMnjwYCpVqsSgQYNYvnw5ERERfPnll1SvXp3Tp0/Tr18/Tp48SePGjbGDUZZ77rmHI0eOcOXKFUaOHMnw4cMBKFiwIKNGjWL16tV07dqV4OBgFi9eDMB3333HzJkzWbRoUSZ/Q1maxCYzmkTSMMa8D7wP0LBhw0RlFCVbEHERLuyFyMvWALt6Bi7+AybaGnDiYQ26sBAIOw5XT8OVE9fO98wH+cpYwyv6qjXaCt4MeYpD4RqQ1xc889p8j7yQrxR45gfvIuCZx6Z55U+3yzHGsGbNGg4cOM/QBx5m1OixaS5LjT5FUXILc4EZwCcxCcaYPjGfReR1IDSZ89sZY05lmHZKlubnn+0+s42/tm0TpvXuDY88ApcvQ9euCfMHD7bbqVPQs2fcvNQsOREWFkZAQABXrlzh2LFjrFu3DoBFixYRHBzMb7/9xqlTp2jUqBGtW7dOsTw/Pz9+/fVX3nvvPaZNm8aHH37IxIkTadmyJS+88AIrVqzg/fffj5WfM2cOxYsXJywsjEaNGnHvvffi6+vLpUuXqF27NpMmTcIYQ40aNTh58iQlSpTg448/ZsiQISlfXO7iKFDB5bg8EOImXRQlbURHwJX/4PweZ1TtrHV3DD8D4Sch7F87Ohd2HM7vtnkFb7XGmHgCHpCvNBSqakfW8pUCr4J2dM27CBSoAPnLg3dRyKJBnwoVKsSQIUPIly/fDZWjRp+iKLmC5Oa/iA3v1xton5k6KdmH556z+4xepy8r4OreuWnTJgYOHMjOnTvZsGED/fr1w9PTk1KlStGmTRu2bt1K4cKFky2vR48eADRo0CB2JG79+vWxn++4447Y0USA6dOnx47gHTlyhH379uHr64unpyf33nsvYCNyDhgwgPnz5zNkyBA2bdrEJ598ghKHZcAIEVkINAFCdT6fkiWIumpH3cJP2flrYcfgwj44+6s17Ew0hB21bpUx5C9vXR7F0xpqHnmt4ebXHAreYkfoClSwxp1H9jdvrly5wpIlS7j99tvTbU519v9WFEVRbpxWwH/GmH1J5BtgjYgYYLbjCpUAnRejpDfJGZn58yef7+d340Zqs2bNOHXqFCdPnozjgumKl5cX0dHRscfx18TLmzcvYAPEREZGxqYntpRCUFAQa9euZdOmTeTPn5+2bdvGlufj4xNnHt+QIUO466678PHxoVevXnh55a5XGhH5HGgL+InIUWA84A1gjJkFfAt0BfYDlwEdClUyjshLzty3y3A2GKIuW4Pu0kFnfxhObbRyAAgUutUac+JljTbfJk5aBetC6VMa8pXNsiNwGcX58+dZsGABlSpVitMhdqPkrhZSURQlcfoBnyeT38IYEyIiJYHvRGS3MWZ9fCGdF6PkNHbv3k1UVBS+vr60bt2a2bNnM2jQIM6cOcP69euZOnUqERER7Nq1i/DwcK5cucL3339Py5Ytky23devWLFiwgHHjxrFy5UrOnj0LQGhoKMWKFSN//vzs3r2bzZs3J1lG2bJlKVu2LC+99BLfffddul53dsAY0y+FfAM8mknqKLmF6Ag4vRVOboSTP9m5cWe22zzvwo4R5w1FaliDDQ8oWhfKdYPaz0PROlnaldLdGGMIDAzE39+f5s2bp+s6o2r0KYqSqxERL6AH0CApGWNMiLM/ISKLgcZAAqNPUXICMXP6wL6AzJs3D09PT7p3786mTZuoW7cuIsJrr71G6dKlAejduzf+/v5UqVKFevXqpVjH+PHj6devH/Xr16dNmzaxI+OdO3dm1qxZ+Pv7U61aNZo2bZpsOf379+fkyZPUrFnzBq9aUXI5xtigJ+d2Ou6We+DCAWfOXKidVxd+xo7g5SsHJZrbwCa3DINCVaBQNfDQiLo3wvHjxylZsiQDBgzAx8cn3ctXo09RlNxOB2C3MeZoYpkiUgDwMMZccD53BCZlpoKKkplERUUlmi4iTJ06lalTpybIe+2113jttdcSpB88eDD2c8OGDQly/E19fX1Zs2ZNbN6bb74Z+3nlysRDkl+8eDFB2oYNG3jggQcSlVcUxYWocMeo+wPO77UjdBHn4fxf1vXy4n4rV6iqHY3LXx6K1wOv1vZzvtJ2hM6nBHgVcO+15ED+/PNPvv32WwYNGkTJkiUzpA41+hRFyRUkNv/FGPMR0Jd4rp0iUhb40BjTFSgFLHZcLLyAz4wxqzJTd8X9vPWWuzVQ4tOgQQMKFCjA66+/7m5VFCXrEBUOx7+H0D/gzK9w9ZwdrQv90wY/yVscitWHAjdBXj+4qTcUugWKN4A86Td/TEk9W7ZsYePGjQwYMCDDDD5Qo09RlFxCUvNfjDGDE0kLwQZAwBjzN1A3Q5VTsjwBCVZvVNzN9u3b3a2CorgPY6yr5elf4PQ2u97cyZ/tPLu8flC6I5Rqa5cnKFDZGnVeNxbyX8kYIiIiGDp0KEWLFs3QetToUxQlWyAiAUB9oDhwBthhjNnhXq2U3MLatXbfoYN79VAUJRcSHQmnNttImCd+hDPbbIRMgPw3QbG6ULga3PogtPgc8pdzq7pKykRFRbFixQoaN26cYuCr9EKNPkVRsiwi4g085mylgX3AeaAwUEVEjgPTgRnGmAi3KarkeF56ye7V6FMUJcMxBo6vtQZeyEq7fl2BylC8vl3SoNqTUO4OyOvrbk2VNBAeHk5gYCB58+bF1zfzfkM1+hRFycr8DvwKPACsN8ZcjclwDMI22LWnfgdquEVDRVEURUkPzgbD4a/h0EIwUVC2M1R/Enwb2ZE8JUewaNEifH196dKlCx4eHplWrxp9iqJkZe41xuxKLMMZ2VsLrBURNfgURVGU7EPYcTi61Bp6/31vl0WIjgDfptDgTSjTRZdAyGGcOXOGIkWK0K1bN/Lnz5+ua/ClBjX6FEXJsiRl8CUi91dG66Io7mBC0IT0La9tyuV5enpSp04dIiMjqVGjBvPmzSN//vypriMkJITHH3+cr776iuDgYEJCQujatSsAy5YtY9euXYwZMyatl6Ao2ZNLh+FQIBxdDKc2AQK+TaBka6j/hl3zrkAlNfRyKIcPH+aLL76gV69eVKxY0S06qNGnKEq2QURaAgOBMsaYu0SkAVDAGKMLpStKOpEvXz6Cg22QiP79+zNr1ixGjRqV6vPLli3LV199BUBwcDDbtm2LNfq6detGt27d0l9pRcmKnA2GP1+x+0uH7Hy8km2hwdtQLAA8vN2toZIJ7N69m+XLl9O9e3e3GXwAmedIqiiKcgOIyP8BS4ErQGsn2aALpSuZwOzZdstttGrViv3793PmzBnuuece/P39adq0Kb///jsAP/74IwEBAQQEBFCvXj0uXLjAwYMHqV27NlevXuWFF14gMDCQgIAAAgMDmTt3LiNGjCA0NJRKlSoRHR0NwOXLl6lQoQIREREcOHCAzp0706BBA1q1asXu3bsB+PLLL6lduzZ169aldevWSeqsKG4j7LgdzdsxGpZXhZX1IPIyBLwCvS/AHTuh0Qw7R08NvlzDqVOn6N+/P7feeqtb9dCRPkVRsgvPA52MMdtEZICTthOo5UadlFxCtVwYQyEyMpKVK1fSuXNnxo8fT7169ViyZAnr1q1j4MCBBAcHM23aNN59911atGjBxYsX8fHxiT0/T548TJo0iW3btjFjxgwA5s6dC0CRIkWoW7cuP/74I+3atWP58uV06tQJb29vhg8fzqxZs6hSpQpbtmzhkUceYd26dUyaNInVq1dTrlw5zp07546vRFESEn4Gjq2G/bPgxHooWgdKtIL6b1nXTe+C7tZQcQPGGNfQ6AYAACAASURBVIKCgrjlllsybUmGlFCjT1GU7EJZY8w257Nx9pGAToBQMpzly+3+rrvcq0dmEBYWRoCzGn2rVq0YNmwYTZo04euvvwagffv2nD59mtDQUFq0aMGoUaPo378/PXr0oHz58qmup0+fPgQGBtKuXTsWLlzII488wsWLF/n555/p1atXrFx4eDgALVq0YPDgwfTu3ZsePXqk4xUrynVgjA3AsutVOL3ZphVvALfcD21WqJGnEBUVxfLlyzl16hSNGzd2tzqxqNGnKEp24YCINDfG/OyS1hzY4y6FlNzD66/bfW4w+lzn9MVgjEkgJyKMGTOGO+64g2+//ZamTZuydu3aOKN9ydGtWzfGjh3LmTNn2L59O+3bt+fSpUsULVo0Qf0As2bNYsuWLaxYsYKAgACCg4MzdY0rJZdzNRT+mQeHv7BunJX6Q9tvIE9xyOQojErWZsWKFYSFhTFw4EDy5MnjbnVi0Tl9iqJkF14ClorIOMBbRJ4CPkfn9ClKhtO6dWsWLFgAQFBQEH5+fhQuXJgDBw5Qp04dnn32WRo2bBg7/y6GQoUKceHChUTLLFiwII0bN2bkyJHceeedeHp6UrhwYSpXrsyXX34JWGPzt99+A+DAgQM0adKESZMm4efnx5EjRzLwihUFiDgP20fB0srwVVE4+DmU7gRdfwf/iXZxdDX4FIdLly4RGRlJ27Zt6dOnT5Yy+EBH+hRFySYYY5aIyCXgceAQ0B4Yaoz5zr2aKUrGkZolFjKDCRMmMGTIEPz9/cmfPz/z5s0D4K233uKHH37A09OTmjVr0qVLF44dOxZ7Xrt27ZgyZQoBAQGMHTs2Qbl9+vShV69eBAUFxaYtWLCAhx9+mJdeeomIiAj69u1L3bp1GT16NPv27cMYw2233UbdunUz/LqVXIgxcPZXCFkFOydC6duh8ftQoiV45XO3dkoW5fTp08yfP5/bb7+dmjVruludRFGjT1GUbINj4KmRpygZyMWLFxOkFS9enKVLlyZIf+eddxKkVapUiZ07d8aet3Xr1jj5gwcPjv3cs2fPBK6jlStXZtWqVQnKXbRoUar0V5TrJjoKDnwIx9fAsTXgXcgaex3Wg19Td2unZHGOHj3KwoULad++fZY1+ECNPkVRsjAiUjY1csaYkIzWRVEURcmBhKyCnZPsPL1qI6HWOChez91aKdmIw4cP061bN6pWrepuVZJFjT5FUbIyR7kWqTMxxMnXCJ5KhvLpp+7WQFGUdCPiPPwzH/a9ZxdNr/U83DwY8pV2t2ZKNmL79u0ULVqU5s2bu1uVVKFGn6IoWZnK7lZAUQAqVHC3Boqi3DDGWDfObY/ZOXq1nodyd4B3YXdrpmQjYtbg++OPP7jvvvvcrU6qUaNPUZQsizHmkLt1UBSAwEC779PHvXooipIGws/AwQXwx3jwLgqtF0PZLu7WSsmmBAUFsX//foYOHUrBgtlnXUY1+hRFyTaISHWgLVAC69oJgDFGl21QMpSZM+1ejT5FyUZER8CetyF4LJRqCy0CoXQHXWZBSRNXr14FoH79+rRo0SLLLcmQEmr0KYqSLRCRfsBc4HfA39nXBda7US1FURQlq2EM7H4d9rwDnj7QdgWU6ehurZRszKVLl/jss8/w9/enSZMm7lYnTajRpyhKduF5YIAx5gsROWuMaSQiQ4Hq7lZMUTKMCRMyvTwRYdSoUbz++usATJs2jYsXLzIhnXWZPHkyzz33XOxx8+bN+fnnn9O1DiWXYQyc/Am2P2mDtTR+H8rcDuLhbs2UbMyZM2eYP38+derUoXHjxu5WJ83oXZBOjB7akbAdM3jz2V5x0p9/sCt/r3mZM5veYPUHI6lxc9zIUHm8vXjj2V4cWTeFUz+/zpdvPUi5kkXjyOxeMZGwHTPibC8+3i2OTPz8sB0zuL9ny4y52FzM9m1befzRh+jQrhV1a1Vj6eKk142aNP5/1K1VjXkffxQnfdjgAdStVS3O9szTT2a06jmBm4Av46V9AgxIzckiMkdETojITpe0CSLyr4gEO1vXJM7tLCJ7RGS/iIxJ8xUoSjYgb968LFq0iFOnTmVoPZMnT45zrAafkmbO/gabh8HisvDj3VC+G3QNhrKd1OBTbpj9+/fTvHlz2rVrh2Rj12C9E9KBxnUqMbRHc37fezRO+lODOzByQHtGvfolLe+byskzF1gx6zEK5s8bKzN19L3cc1sAg8bOpcPQNylcwIevpz+Eh0fcP9XLs7+lUoexsduUDxIuXPvwpAVxZOYv35IxF5yLuXz5MrdWqcqzY57Hx8cnSbnvVq9i584/KFGyZKL5d3fvwfdBG2K3/43XKWmp4BxQxPn8n4jUAIoDBVJ5/lygcyLpbxpjApzt2/iZIuIJvAt0AWoC/UQk666+qig3iJeXF8OHD+fNN99MkHfy5EnuvfdeGjVqRKNGjdi4cWNs+u233079+vV58MEHqVixYqzReM8999CgQQNq1arF+++/D8CYMWMICwsjICCA/v37A8QGROjTpw/ffnvtVhw8eDBff/01UVFRjB49mkaNGuHv78/s2bMBOHbsGK1btyYgIIDatWvz008/ZdyXo2QtIi/B7xNgVX07T6/eNLj3BNQZD16pfTQoSuLs27ePPXv20LhxYxo2bOhudW4YNfpukMIFffj45UE8NPEzzp0Pi5P36P+1Y9rH37Hk+2B2HTjG/S98SsH8eenTpWHsuYPvacZzby5m3ZbdBO8+yrBx86hTpSztm8T1WLt4KZz/Tl+I3S6FXU2gS+iFsDgyV8IjMu7CcymtWrfh8SdGcXunzkgSvYchIf/y6pSXmfLa63h7eScq4+OTD78SJWK3QoUKZaTaOYW1QHfn8xfO8S/AytScbIxZD5xJQ72Ngf3GmL+NMVeBhcDdaShHycZ89ZXdcguPPvooCxYsIDQ0NE76yJEjefLJJ9m6dStff/01999/PwATJ06kffv2/Prrr3Tv3p3Dhw/HnjNnzhy2b9/Otm3bmD59OqdPn2bKlCnky5eP4OBgFixYEKeOvn37EuiES7169Srff/89Xbt25aOPPqJIkSJs3bqVrVu38sEHH/DPP//w2Wef0alTJ4KDg/ntt98ICAjI4G9HcTtRV+G3cbC8GhxfA13/hCYfQuX+4JH4c1dRrocdO3awdOlSChTIOZ0HOqfvBnl3XD8Wrw3mx617eW74tfC/lcr5UqZEEb7f9Fds2pXwCDb8up+mdW/mo683Uq/GTeTx9mLt5t2xMkf/O8fuf/6jad3KrHU5d+TA23h6aEeO/neWRd/t4M15a4mIjIqjy7TRPZn+XF8OhZxm7pJNfPT1RoxJbl1rJb2JjIxkzOinGP7gw9x8yy1Jyq1euYLVK1dQ3NePlq1a89Ajj1KgQPYJ++sOjDFDXQ7HA7uBwsC8Gyx6hIgMBLYBTxljzsbLLwcccTk+CiQ6i1tEhgPDAW666aYbVEvJSvj5uVuDzKVw4cIMHDiQ6dOnky9fvtj0tWvXsmvXrtjj8+fPc+HCBTZs2MDixYsB6Ny5M8WKFYuVmT59emzekSNH2LdvH76+vknW3aVLFx5//HHCw8NZtWoVrVu3Jl++fKxZs4bff/+drxzrOzQ0lH379tGoUSOGDh1KREQE99xzjxp9OZ2TG2FDbzuSV28qVOyr0TiVdGX79u1s2LCBIUOGJNtWZTfU6LsBhnRvzs0VSjB03CcJ8kr72YU+T5y5ECf9xOkLlHXm7JX2LUxkZBSnzl6MJ3OeUr7XFgp97/MfCd59hDOhl2hYuyIvPnY3lcr58sikz2JlJr73Deu37uXi5XDaNanGlFHd8S1agFc/XJ1u16ukzMx336FIkaL07vt/Scp06XonZcqWpWTJkuzfv5/pb73O3j27mf3hx5moafbG2N6Mz1IUTJmZwIuAcfavA0PjyST2NpFob4ox5n3gfYCGDRtqj0sOYu5cux882J1aZC5PPPEE9evXZ8iQIbFp0dHRbNq0KY4hCCTZwRgUFMTatWvZtGkT+fPnp23btly5ciXZen18fGjbti2rV68mMDCQfv36xdbxzjvv0KlTpwTnrF+/nhUrVjBgwABGjx7NwIEDr/dylazO5aOw82X4+2Pwnwg1Rut8PSVdiY6OJjIykipVqlCtWrVstQZfatC7JY1UqViSiY/dxZDn5yUYcXMl/oNQRFIcfROROG+U0+evY/22fezcF8LcxZt44pVAhnRvTvEi14acp3ywip+D/+b3vf/y9qfrmDx7JU8O7JCma1PSxratv7B0ySImvjQ5WbmevfvQomUrqlStRpeud/DatLfYvOln/tr1ZyZpmj0RkdUi0j5eWnsRSTjBNZUYY/4zxkQZY6KBD7CunPE5ClRwOS4PhKS1TiV7MnfuNcMvt1C8eHF69+7NRx9dC0bVsWNHZsyYEXscHBwMQMuWLfniiy8AWLNmDWfP2gHz0NBQihUrRv78+dm9ezebN2+OPdfb25uIiMSnIfTt25ePP/6Yn376KdbI69SpEzNnzow9Z+/evVy6dIlDhw5RsmRJHnjgAYYNG8avv/6ajt+CkiU4+TMsrQzhJ+HuQ1DzWTX4lHQlIiKCwMBANmzYQOHChXOcwQc60pdmmvhXpkSxQmz/8lq4aS8vT1rWv4X7e7akfs+XASjlW5ij/52LlSlRvGDs6N/x0+fx8vLEr1jBOKN9JYoXYsOv+5Ose+vOgwDcUsGPM6GXEpX5ZedBihTKR8nihRKMNioZw9ZftnDq5Ek6tL0WNTUqKoq33pjG/E/n8d26xJeTq1W7Np6enhw6dIgaNWtllrrZkQYkXJPvJ+z8vjQhImWMMcecw+7AzkTEtgJVRKQy8C/QF0h6KFdR0pP0XrLhOnnqqafiGHnTp0/n0Ucfxd/fn8jISFq3bs2sWbMYP348/fr1IzAwkDZt2lCmTBkKFSpE586dmTVrFv7+/lSrVo2mTZvGljV8+HD8/f2pX79+gnl9HTt2ZODAgXTr1i12AeT777+fgwcPUr9+fYwxlChRgiVLlhAUFMTUqVPx9vamYMGCfPJJQu8bJRtzZBFs/D9oOgcqpypYs6JcF5cvX+bzzz+nePHitGnTxt3qZBhq9KWR5T/8TgPHsIvh/Yn3sf/wSV77aDX7Dp3g2MlQ2jetzvZddkJ73jxetKh3C8+9tQSAHX8d5mpEJLc1qU7gqm0AlCtZlOqVS7H5t3+SrNu/WnkAjp86n6RM3arlCbtylXMXwpKUUdKX3n3/jw4d47odPTx8GF263sm9PXslcRbs27uXqKgoSpQokdEqZneiAW8g0iXNi8TdLxMgIp8DbQE/ETmKnRfYVkQCsO6aB4EHHdmywIfGmK7GmEgRGQGsBjyBOcYYHZZVciwXL17rhCxVqhSXL1+OPfbz84sNsuJKkSJFWL16NV5eXmzatIkffviBvHltpOqVKxOPtfTqq6/y6quvJlqvt7c3p0+fjiPv4eHB5MmTEyz1MGjQIAYNGnQdV6hkG/6ZD9sehfZroaQuQ6VkDPv27aNixYrcdttt2XpJhpRQoy+NhF4MI/RiXIPqUthVzoZeYtcBO3Dw7mc/8MywTuw9+B/7Dp1gzAOduRR2lcCV1sA7f/EKc5dsYvKT93Di7AXOnLvEq0/14I99IazbYoO7NPGvTOM6lfhx615CL16hYa2beO3pe1ke9DtHjlv3ma6ta1PKtzBbfv+HsPAI2jSqwv8evoM5izZyNSISJf24fOlSbFQ6Y6I5diyE3X/9RZEiRShTtmyCCb/eXt74+flRqfLNABw5fJgV3yyjVes2FC1WjL8PHOD1qVOoXqMmAfXqZ/r1ZDO2A48Br7mkjQBS5ctljOmXSPJHiaRhjAkBurocfwskWM5BURTL4cOH6d27N9HR0eTJk4cPPvjA3SrleESkM/A2tjPqQ2PMlHj5RYD52DVOvYBpxpjsM3n86FL49Qlotwb8Eo2dpSg3xLFjxzh79ix169Z1tyqZghp9Gcjrc9fikzcPb47pTbHC+dm68yB3PjyDi5fDY2WemfY1UVHRfDplKPnyevPDL3u4/3+fEB1tZ/WFX42gZ8f6PPdgF/J6e3H42BnmLPqZN+Z9F1tGRGQUw3u34tWneuDhIfxz9DQvzlzBrC8SdydU0s6ff+7k/iHXAgTMfPcdZr77Dt3u7s6Lk6ckc6bF29ubX7Zs5rP5n3L58iVKly5DqzZteOjhEXh6emak6jmBZ4EgEbkX2AtUAaphR+8URXEjVapUYceOHe5WI9fgsn7o7dh5x1tFZJkxZpeL2KPALmPMXSJSAtgjIgucpWeyLsbA3ncheDS0CFSDT8kQ9u/fz+LFi7nzzjvdrUqmIdkhpH++eiOyvpJKqjm7dUbKQkq2wscrdS6WN4qIlAYGAJWw7pjzXebkZSkaNmxotm3bljAjuTlabp6/pSRNjIdj/vwZW89ff/1F9erVc7SLUWZjjGH37t3UqFEjTrqIbDfGZMsVl0WkGTDBGNPJOR4LYIx5xUVmLDYI1aPYNvM7oKoTuCpJkmy7MoPLR+1yDJePQssvwK9pyucoynWyZ88eli9fTu/evbPd8ko30m7pSJ+iKNkGY8xxYKq79VByHxlt7MXg4+PD6dOn8fX1VcMvHTDGcPr0aXx8fNytSpKI/aFLX2cHVmrWD50BLMNGGy4E9EnK4MsSa4yGHYcfukCJlnDbD+CZ1z16KDkWYwyRkZGUK1eOQYMG5bpYCpli9IlIdeBubCNlsA3QMmPMX8meqCiK4iAijwIbjTHBItIA+Bob1KWvMcZN3dJKbuG99+z+kUcytp7y5ctz9OhRTp48mbEV5SJ8fHwoX768u9VIgIgUxM7J6w9EAQVE5B6grjFmYkqnJ5IW3yuqExAMtAduAb4TkZ+MMQmiwLl9jdHQXbDudqjQExq8qcsxKOlOdHQ0q1atIjIykm7duuXIJRlSIsONPhF5FugHLAR+cZLLA5+LyML4E48VRVGS4CmuLc/wEhAIXMAuqJ5zYywrWQJnCboMN/q8vb2pXLlyxlaiZBVeB0oBLYC1TtpWYDKQktGXmvVDhwBTjJ3Hs19E/gGqc+1dLGvwXxD80Bmqj4KA5Ne5VZS0EBERwaJFiwgPD6d3797uVsdtZMZI3zCgljEmzgqsIvIG8CeQqNHn6mrgVb4tXn66fpmi5HJ8jTEnRSQv0By7rl4EMMq9aimKoqSJO4GaxphQETEAxph/nSVjUiI164ceBm4DfhKRUtjAV3+nm/bpwfl98ONd0HwB3HSvu7VRcih///033t7e9OzZM1cHzcsMoy8aKAscipdexslLFFdXAw3koigKcNF5GaoD/G6MuSIiebDhyhVFUbIbAsRZ+8lx+byYuPg1klo/VEQecvJnAS8Cc0XkD6euZ40xp9L5GtKOMbBlKFR7Qg0+JUM4d+4cISEh1KxZk6pVq+b6edKZ4TT9BPC9iKwUkfedbRXwPTAyE+pX4hG2YwbdOwS4W40MY+svW6hbqxpnz55xtypppsvt7Zn3caJLyMWydPEimjasl0kaZQnmAluAT4F5TlojYL+7FFIURbkBNgJj46U9BvyQmpONMd8aY6oaY24xxrzspM1yDD6MMSHGmI7GmDrGmNrGmPnpqv2NEHUVtj4M4aegznh3a6PkQI4fP86cOXO4cOECQK43+CATRvqMMatEpCrQGBvIRXDWlDHGRN1I2WE7kg/9/+myzQwfnzlt3E1lirPn20mcPneJmneN5/zFK7F5qz8Yya79ITz56peZoksM70+8D9+iBbl35Kw46ZU6jOXs+bAkzsoa/O+5MSxbujhBeuBXS6geL+y2Oxg2eADbttppEd7e3pQpW4677+nOkGEPpIvrwILAr8iXL1/scd1a1Zj2xtvc3qlzbFqnLl1p2Tr3TGUzxjwvIkHAVWPMj05yOPC0+7RSFEVJM6OAdSJyH1DQGZHzxrpk5lzCz8CGXhB5CW4LAg8NJK+kL0eOHGHhwoV07dqVWrV0elgMmXKnOSGCN6d3uZU6XOsg69K6NjNf6B8nLSw8zjRCvLw8iIxMdnmaGya/jzdPD+nIC+8sy9B6boT/Tl9wtwqpommz5rz8ymtx0ooWK+YmbRJyd/cePD5yFOFXw1kfFMSrr7yEh4cHQ+8ffsNlFy9ePEUZHx+fLB2GPCMwxnwX71ijdiqZQlCQuzVQchrGmCMiUhs7t68ydhrMN8aYrN0reyNEnIdv/aFwNWi3CvIUdbdGSg4jKioKX19f+vbtS4UKFVI+IReRrWPi/nf6QuwWeiEsTlrePN7899M0enduwMrZj3Fm0xvcf29L7rurCSc3vh6nnFYNqhC2Ywa+RQvEpjWtW5k1H47k9M9vcGD1S7z9XB8KFUj5Bfu9z3/k0X5tKVuiSLJyowZ14M9l4zmz6Q22fvEcfbs2ipPfqHZFfv7sWc5ufpNNnz9Lp5Y1Cdsxg1YNqgDg4SHMHP9//PXNBM5seoM/lr7AqEEdYoevn3+wKwO6NaVr69qE7ZgR51xX986geU8xZVT3OHUXKuDDmU1v0K2dPwDeXp689Pjd7F/1Iqd+fp0N80fTodm10TYvLw9ef6Ynf695mXNb3mTfyhd58fFuKX5XKeGdJw9+JUrE2by8vPhk7sf07H4XTRoG0KFdKya88DznzyeIQB3LhQsXeG7MaNq2akajenXo2uk25n8yN07+pPH/o22rZjRrVI+hg+7jz51/pKifj08+/EqUoFy58vTrfx9Nmjbjh3XfA3A+NJRxY5+lZbNGNK7vz/Bhg9m/f1+qdXJ17+xye3sAnh41krq1qsUeu7p3Hjz4D3VrVWPf3j1xdPzqi0DatGhCRITtADmwfz8jHh5Os0b1aNuqGc8+PYpTLqHh9+3dwwNDB9G8cX2aNapHr+7d+GVLuvfXKIqi5HpEZIAxJtwY87UxZpox5ktjTJiI9He3bhmCMbB5KJTpBLd9rwafkq4YY9i4cSNfffUV+fPnV4MvEXL8mPqkx7ox9s3FPDTxMyIjo2jXpFqK59S6tSzL3xvBS7NW8PCkzyheOD9TR/dk9oT+/N/o5OdZLVq7g9YNq/C/R+7g4YmfJSoz4dG76N4hgCemfMHegydo6l+Zd1/ox7nzl1m14U8K5MvD19MfYt3mPQwbN48yJYoydXTcSc4eHkLIiVDue2YOJ89epFHtisz4Xz9Oh15i3pJNvPXJWqpXLkWxIgUYNs5OfzoTejmBLp+v2Mozwzoy9s0l2KjOcM9tAYSFR7Dypz8B6yZ6c3k/Bj03l3//O0fnlrX4+u0HaXnfVP7Y+y+P9mtLt3Z1GTBmDodDzlCuVFGqVCyV4vecVjw8hNHPPkf5ChU4FhLClMkvMmXyi0yekvia3TOmv8X+vXt5593ZFPctTsi//8bO9zPGMOLh4RQqVIh33p1NkSJFWLZ0MQ8MHcTSFasoUaJkqvXKmzcv58+HAvC/58dw8OA/vP3OexQuXJh33n6TRx68n2UrVuPj45OsTvFZEPgV7Vo1Y/zEl2jdpi0eibiPVqpUmVq1arPim+U8Meraf/zbFcvp1Lkr3t7enDx5gqGD+nNPj56MevpZIiMjeOftt3h8xMPM//wLPDw8GPPM01StVo0FC7/E09OLffv2kjevLpCrKNOm2f3T6kyspB/vYucox+cdYEEm65Lx7H0Xzu+GTlvcrYmSw4iOjmb16tUcPHiQ/v1zZp9JepDjjb6ZC39k8drg6zrnyUG38dWa7bz96ToADgCPv7yQLYFjKVGsICfPJh9Y67m3l7By1mNM/3Qdf/19PE5efp88PH5fO+565F027jgAwKGQ0zSsXZEH+7Rm1YY/6du1EZ4eHjw0cQFXwiP46+/jvPbhaua+Mji2nMjIaF6cuSL2+PCxMwTUqEDvzg2Yt2QTl8KuEhYeQf6rkcm6c365ejuvPd2DNo2qEPTLXgD6dm3Iou92EBEZReXyfvTu3IDqd4znyPGzAMwKXE/7JtUYdm8LnnjlC24qU5x9h06w8Vd7PUeOn2Xzb/+k7stOhp83/BQnUEn9Bg14b/aH3Dfw2vdQrlx5nhw1mpGPPcJLk1/FwyPh4PWxkH+pVqMmdfz9Y8+J4Zctm9mzezdBGzbFukqOePwJ1gf9wDfLljJk2AMp6hkdHc2mjRv4eeMG+g8YxKFDBwn6YR1z5s2nQUM7gvvylKl07tCWb79ZTo+evZLVKT4xrp6FChXCr0SJJOXuuKsbn86by8gnn0JEOH7sGL9u38bIJ58C4IuFn1O1WnWefGp07Dkvv/IqrZo35s+dO6nj78+xkH8ZNHgolW++BYCbKlZM8foVJTfwzTd2r0afko4kiCwhIpWAyEzXJKM5vw9+GwO3/wxeBVKWV5Tr4MiRI5w4cYIhQ4bkumkv10OON/q27zp83efUq3ETt1Two2fHBrFpMUF/bq5QIkWjb8P2/Xy36S8mPX43vZ6YHSevxs2lyeeTh6XvPoJxWYjC28uDQyF2pKdapVLsOnCMKy5zEn/ZeTBBPff3bMng7s25qUwx8uXNg7eXB4ePnb2uaz0Teonvfv6Lvl0aEfTLXkr7FaZNw6pMnr0SgHrVK+Dh4cGvX4+Lc15eby+Ctloj8dNlm/lm5mP8sfQF1m7azeoNf7J6467YkcO0Ur9BQ16Y8OK1Op0becvmTcz58H3+/vsAFy9cIDo6moiICE6dOknJkglHGHv37cdTT45k964/adq8BW3atqNho8YA/LXrT65cCaNty2Zxzrl6NZwjR44kq9/XX37BsiWLY10n7+zWjYceGcGWTT/j4eGBf91rEVILFSrErVWqcuDA/hR1Siudu97JG9Ne49ft22jQsBHfrlhO+fIVqBtQL/Zaf92+LdGIn0ePHKaOvz8DBg1h4vhxLFu6mCZNm9Hh9o6xBqCiKIpy44hIBGAATxG5Gi/bE3gv87XKQM79ARv7MPcqUAAAIABJREFU2qUZivm7WxslBxEWFsbBgwepUaMGAwcO1AidKZDjjb7LYXHb02hjiP+f8PaK6y7nIcLHizfxzoJ1CcoLORGaqnrHvb2UXwLH0qJe3BdmDw9b+b0jZ3PkeFx3vshIG8xURFI0mHp2rM/Up+9l7JuL2fzb35y/dIWHeremW/u6qdLPlYXfbmXGuH6MfCWQ3p0bcvS/s7GjkB4eQnR0NC3ve42IyLjBVq9cscZO8O6jVL/jBTo2r0mbxlX5YNIA/tj7L3c8POOGDD+ffPkSjDSFhPzLY488SI+evXlkxOMUKVqUv3btYszoUbHGV3xatmrDqu/WseGn9fyyeTMjHn6Q2zt15sWXXyE6OhpfXz8+/iShJ02BggWT1a9Tly489PAI8uTJQ4mSJWOjdhqSvuaYBik5ndKKr68vTZo2Y8U3y2ONvq533hWbHx0dTavWbRj19LMJz/XzBeDhRx+j6513seGn9WzauIFZ773LuPET6N6jZ5r1uhFEZE5q5IwxQzNaF0VRlHSiA3aU71ugi0t6NHDcGLMv0bOyI6e3wZomUGci1Ez47FGUtBIaGsqCBQu49dZbqVGjhhp8qSDHG33xOXX2IgXy5aVQAR8uXLLLKtStVi6OTPDuI9S8pQx/H0n7Gqa7DhxjwTe/8PIT9xB+9Zqnxl9/H+dKeAQ3lSnOj85IWXx2/3Oc/7uzMT55vWNH+xrVjmv8NK93C1t3HmRW4PrYtMoV4rr+XY2IwtMz5ZtgedDvzBjXj66ta9OnS0MWfnstIGLw7qN4eHhQyrcw67cl/Ry6eDmcRWt3sGjtDuYv28z6T0dzS4US7D98IsX6r4ddO3cSERHB6GfHxhpZ61MRVq9Ysf9n776jo6q+No5/NymEmgCh966IFEF670WahSYgIFIFFVGaShGx8CodERVFRARFBRH5ASqKitIUBaRLCzX0AIGE7PePmcQkJCSk3ZT9Weuumbn1yQBhzpxz98lNu/Ydade+I3XrN2DUc8N5cdwE7q5wD2fPBpIpUyaK3OFNv9mz54hx+GOp0mUICwvjr+1/RgzvDAoKYv++vXTo9GCcmby9vW85p6enFzfD4q4827Zde157ZRIPP9KZfXv38ua0mRHb7q5wD2tWf0vBQoXw8vKK9RzFi5egePESPNqjF5MmjuPLZZ871ugDIn/T4AN0ATYB/+KqdlcD+NSBXMYYkyDhU86ISGlVPeF0nmRz8wZs7AFV/w/uesbpNCYdCQwMZOHChdSqVYvatWvHfYAB0nj1zoTY/Pchgq5eZ+LQ9pQq6k/HplXo37l+lH3e/HAt1e8pzoyxXalcvgilivrTun5FZo7tekfXevntlVQqVzhKgy3o6nWmffQdrz7TiV4dalGqqD+VyhWm38P16PtgXcDV83YzLIw5L3bjrlIFaFyzPM/1bQn814u07/BpqtxVlBZ1K1C6WF5GPdGK+veViXL9w8fPck/pQpQtno88ftnw9Iz5j/v6jVCWf7+dkf1acV+FYixetSli2/4jp1n8zSbendiTTs2qUKJwHu6rUIynezalg7tXcViPJnRuVY3yJfNTqqg/XVpX5+LlawScvrOhpvFRrHhxwsLC+HjhAo4dO8q336xk0cIFtz1m9szpfP/dOg4fPsTBAwf4bt0aihQpire3N7Vq16FK1ft4auhgft7wI8eOHWX7n38wZ9YMtm1N2GwAxYuXoHGTprw84SW2bd3Cvr17GDNyBNmyZ6dN23ZxZopJocKF2fTbRgLPnOHSxdh7m5s0bU5oaAjjXxxLxXsrUbx4iYhtXbp153LQZZ4f8Qx//bWdY0eP8tvGX5k47kWuXAkiODiYyS9PYPOm3wkIOMZff23nj23bKFXaueGdqvpE+IJrONTjqlpPVXuqaj3AevhMisiSxbUYk1RU9YSI5BGRViLSU0R6hS9OZ0sS++e6KnaWf9rpJCYdCQsLI3v27LRp08YafHcow/X0nb90lT5jP2Ty0514rEMtft52gAlzvuGDVx6L2GfHvuM07zeNcYMfYM17T+HhkYl/j51lxQ/b7+hax05dYM7iH3m2T/Mo6yfMWcnpc5d5uldTZozpwqUrwfy1J4C3PlwHwJVrN3j4qXeYPqYLvy0eyT8HT/LKO6tY/H/9uO7u+Xvv85+pVL4wH07ujQh89d2fTP/4Ox7r8N8/gA++/JUG1cvyy6LnyZHNhxb9prNha8y9dZ98s4leHWqxbdcR9vx7Ksq2/uM/ZuTjrXjlqY4Uzu/HuYtX2bLzMD9ucfVUXr4SzNO9mlGmWF5Ule17jtFx6ByuBcc83DIxypW/i+dHj+WD999l9oxpVK5SleHPPc/zz8b+LaK3tzczp0/leMAxvL0zU6lyZWbMdk1YLyLMnjuPWTOmMWHci5w7e448/nmoUvU+2rXvmOCcEye9yhuvTWbYk4O4cf06Varex5x33ou4wfh2mWLy7HMjefON12jZrBH58uXn27W3Dj0GyJIlC02aNWfliuWMHBP1Psx8+fKz4OPFzJj6FoMH9OPG9esUKFiQ2nXq4e3lamxeunSJF8eMIjDwDH5+fjRo2Jjhz6WaITntgd7R1i0GZqV8FJPRfPut0wlMeiMizYBlwA3AD7jgfvwX+MjBaIl35hf4cxQ0Wcst99QYk0A7duxg27Zt9OzZk/Ll467Gb6KSxBbbSAlZqj6Z+kMmswca3cuSN5+gWNPRnL1wxek4iXJ+s31GT298PG+tQpfURGQ/0F9Vv4+0rjHwvqqWSu7r36nq1avrli0x9BaPHx/7QbfbZoxJUiKyVVWrO3j9LcBiVX1TRM6rai4ReQkIUtW3nMoV6++u+AoLgZV3QfmnoPywpAtmMrSNGzfy22+/0b17d/LnT75pwVK7xPzeynA9fWnFo+1qcuhYIEdPnueeMoWYMuIhvvlpR5pv8BmTCJOBlSLyGXAIKAE8DAx1MJPJIF52FxJ+8UVnc5h0pSwwzf08/Iuz14F9gGONvkTb9TpkKQjl7FezSRqnT5/mzz//pG/fvvj6+jodJ82yRl8qlT93Dl4c2IYC/jk5dfYy327YwQvTlzsdyxjHqOp8EdkH9ATuBwKAVqq6IT7HuyuBPgCcVtWK7nVTgHa4hlcdAPqo6oUYjj0EXMZVWCbUyd4B44zvvnM9WqPPJKGrQGb341kRKQacB3I5mioxQi7B7qnQ7Ecb1mkSLTQ0lIMHD1KuXDkGDBgQ41zMJv6s0ZdKvbVgHW8tWOd0DGNSFXcDL16NvBh8iOv+v8j3yqwFRqtqqIi8DowGYruJsbGqJrykrzHGRPUr0BH4BNf0DSuA68BGJ0Mlyu7p4F8b/Co6ncSkccHBwSxZsoQsWbJQtmxZa/AlAWv0GWPSDBGpB/QCCqpqOxGpBmRT1Z/iOBRV/UlESkRbtybSy99wDRc1xpiU0IP/qqg/BzwL5CCtDu1UhYPzoc6t894acyeCgoJYuHAhxYsXp1WrVjYHXxKxZrMxJk0Qke64vgkPBhq4VyswMYku0ReIrUajAmtEZKuI9L9Nxv4iskVEtpw5cyaJYhlj0iNVvaaqV9zPg1X1FVUdBdzlcLSEObEaPDKDfy2nk5g0TFVdU2rVqkXr1q2thy8JxeudFJEhIlLF/byaiBwWkf0iYve1GGNSylighaoOA8Jnqt8B3JPYE4vIWCAUiO0r6rqqeh/QGhgiIg1i2klV56lqdVWtnjdv3sTGMqlInjyuxZikICLZReQ+EckTaV1lEfkWWHObQ1OvA/Oh7GAQ+5BuEubw4cMsWLAAT09Pqlataj18SSy+/zKfxVU0AWAS8Cmu+2PeTIZMxhgTk0KqGl5HPHwal1DAIzEnFZHHcBV4eVRjmcNGVY+7H08DXwI1EnNNk/YsW+ZajEks91QzAcAW4KiItBGRl4Hf3evTXk/f6Q1wcg2UeNTpJCaN2rVrF0uXLqV+/frWu5dM4ntPXx5VPSMimYE6QCcgBBiebMmMMSaqAyJSR1V/jbSuDrAnoScUkVa4Crc0VNWrseyTDcikqpfdz1uQdENKjTEZzyTgXWA+0B9YCPwD3Kuq+5wMlmA7X4HKkyGzdYebO3fp0iXWrl1Ljx49KFiwoNNx0q34NqWDRKQQ0Aj4S1WDcX27nqhv2I0x5g5MApaLyAuAl4g8Cywmng0wEVmMqypeeRE5JiKP46rmmQNYKyJ/ishc976FRGSV+9D8wM8ish3YBHyjqquT9Cczqd7o0a7FmCRwF66qwbuAMYAf8FCabfCdXAdnN0PJXk4nMWmMqnLw4EFy5szJkCFDrMGXzOLb0/chrmEHmXH9ggLXPFn7kyGTMcbcQlW/EpErwDDgMNAE6Kuqa+N5fLcYVr8fy77HgTbu5weBygkKbdKNjWm3iL5JfbxUNQRAVa+KyEVVPeV0qATbMxPuega8cjidxKQhN2/eZPny5Zw/f57ixYvj6WkTCiS3eL3DqjpWRNYDN1T1R/fq68CI5ApmjDHRuRt48WrkGWNMKuUlIt0AieU1qvqJI8nuVNBBOPUD1JrvdBKThly/fp2lS5fi5eVFr1698PCwgYMpId7NalVdKy4FVfVEpIIKxhiT7ERkG/CBqs6Mtv5nVa3nUCxjjLlTp4DJkV4HRnutuCZsT/22j4VSfexePnNHMmXKRJkyZahZs6YVbUlB8Wr0iUh2YBquiURvAtlEpCNQWVUnJGM+Y4wJdw8wXESKq2rkUQaVnApkjDF3SlVLOJ0hSZzbCgFfQ8ejTicxaURgYCCrVq2iW7du1K5d2+k4GU58m9dvAgWAusAN97rNQJfkCGWMMTG4DtQGmojIpyLi5XQgk3EUKeJajDFu20bAPS+Ady6nk5g04OjRo3z44YdUqlQJLy/779sJ8R3e+QBQQVUviogCqGqAu6KnMcakCFU9KSINgc+BdSLSwelMJmP4+GOnExiTilzaA2d+hsbfOp3EpAHBwcF8/vnndOzYkTJlyjgdJ8OKb0+fANeirHAN+QxK8kTGGBMzAVDVy7gqax4AfgXsK0NjjElJpzdAoTbg4eN0EpPKHTt2DB8fHwYPHmwNPofFt9H3CxB9hqKhwA9JG8cYY2IVUbVTVW+qal9gKXDSuUgmo3j6addijAFOroVCrZxOYVIxVeW7777jyy+/5Pr162TOnNnpSBlefId3Dge+F5EeQHYR+RvXt+tNky2ZMcZEoqoPxrBuPDA+xcOYDOfPP51OYEwqcTMYTvwPqr7hdBKTSt28eZOvv/6awMBA+vbtaw2+VCK+8/QdFZGKQDugBK6JkVeq6rXbHmiMMYkgIo+o6mfu591j2U1VdXEKxjLGmEQTEQ9co6geA/Kpqq+ItARKqupcZ9PdxvHV4FcJshV3OolJxfz8/GjTpg3e3t5ORzFudzJP33VcxROMMSaljAM+cz9/JZZ9FLBGnzEmrXkZaAaMBMJnN98LvAak4kbfStf9fMZEExQUxMqVK2nfvj2NGjVyOo6JJr7z9M2LbZuq9k+6OMYY8x9VrRjpeUknsxhjTBLrDtRW1RMi8p573SFcI6pSp5AgOLwUHtjtdBKTypw9e5ZFixZRqVIlsmTJ4nQcE4P4FnLxirYUB3oC9qdqjDEm3StXzrUYk4SyAaejrfMGguNzsIi0EpE9IrJfREbFsk8jEflTRHaKyI+JzAunvodclSGrzdhl/hMaGsqiRYuoV68ejRo1QkScjmRiEN97+vpEXycinYAWSZ7IGGPcbjfKIDIbcWCS27x4/U005o5sBfoA70Va1x3YFNeB7vsBZwPNgWPAZhFZoaq7Iu3jB8wBWqnqERHJl+jEJ9dCfqvhZ/5z6tQp8uXLR79+/ciaNavTccxtxLenLyZfAV2SKogxxsQg+iiD2BZjjElrRgCvicg6IKuIfA1MxnWPX1xqAPtV9aCq3gA+BTpE26c78IWqHgFQ1ei9infu5DqbqsFE2Lp1Kx9//DFBQUHW4EsD4l3IJQatiTZhuzHGJKWYRhkY44T+7r5k6/EzSUVVd4hIBVy3y+zGVRm9n6qeisfhhYGjkV4fA2pG26cc4CUi64EcwHRV/SjBgS/uhku7IU+NBJ/CpA+qyvr16/n777/p3bs3OXLkcDqSiYf4FnLZh6tCXrhsQD7gqeQIZYwxxqQme/c6ncCkNyKSxd379mZCDo9hnUZ77QlUwzWnchZgo4j8pqq3/G0Wkf5Af4BixYrFfMVjX0DZwSCJGSRm0gNVJTQ0lL59+5I9e3an45h4im9P36Ror4OAP1T1YBLnMcaYGIlIXmAarg8weSNvU1UPR0IZY0zCnRKRJcD7qvrbHR57DCga6XUR4HgM+wSq6hXgioj8BFTGNS1EFKo6D5gHUL169eiNR5eT30HZQXcY06QnN27cYNWqVTRu3JjmzZs7HcfcoXh9XaOqC6Ity6zBZ4xJYTNwDWl6HLgCtAd+BZ52MpQxxiRQB1z3JK8VkX9E5HkRKRDPYzcDZUWkpIh4A12BFdH2WQ7UFxFPEcmKa/jnPwlKqgpnN9nQzgzsypUrLFiwABGx3r00KtaePhGpE58TqOqvSRfHGGNi1QS4V1VPi0iYqn4jIn8DnwMzHc5mjDF3RFV/AH4QkSdxFcZ7DHhZRFaravSiLNGPDXUf9z/AA5ivqjtFZKB7+1xV/UdEVgN/AWHAe6q6I0FhrxwCrxyQLZahnyZdU1UWLVpEmTJlaNy4sU3JkEbdbnjnz/E4XnH9sjHGmOTmBZxxP78mItncZcjvcjKUyRiqVHE6gUmvVDUIeF9EtuG6neaBeB63ClgVbd3caK+nAFMSHfL8dvC9N9GnMWnP+fPn8fPzo2vXruTMmdPpOCYRYh3eqaqZ4rFYg88Yk1L2Ave5n28HxojI80B8Kt0hIvNF5LSI7Ii0LreIrBWRfe7HXLEcG+ckyCZ9mzbNtRiTlEQkj4g8JSJ/4vqy/TzQ0uFYtzr1A+SN1wAwk47s27eP9957j8DAQGvwpQNWgskYk1aMATJHev4I8AwwPJ7HfwhEn2BqFPCdqpYFvnO/jiLSJMitgQpAN3eZdWOMSTAR+QIIwHU/3ttAIVXtoarrnE0Wg4CvIV8Dp1OYFPTHH3+wfPlyunbtSt68eeM+wKR68Z6nT0Sa81/VvIjBvKraNxlyGWNMFKr6faTn23DNQXUnx/8kIiWire4ANHI/XwCs59aJkSMmQQYQkfBJkHfdyfVN2tajh+vx44+dzWHSlQNAVVVNWHGVlKJhEHwKct0X974mXVBVTp8+Te/evfH393c6jkki8erpE5GncFWBKg10xzXJZ2cSN7m7McbcMRHJISKFIi+JOF1+VT0B4H7MF8M+MU2CXDiWbP1FZIuIbDlz5kxMu5g06tgx12JMUlHV51J9gw/g0h7InAe8fZ1OYpJZWFgYa9as4dy5c7Rs2dIafOlMfBttTwJtVHW9iJxX1UdEpC3wYDJmM8aYCCJSF/gA15dPEatJ/oJS8ZkE2bUyPnNdGWMyLBGZoarD3M/nxbafqvZPuVRxCPga/Co7ncIks5CQEJYtW0ZISIhNyZBOxfeevgKqut79PPyDzCpcQ5yMMSYlvAt8BlQESrmXku7HhDolIgUB3I+nY9gnPpMgG2NMfHhFex7bknpcOQy5rNGX3n322WdkzpyZ7t27kzlz5rgPMGlOfHv6TotIflU9BRwTkZpAIFYIxhiTcgoDL6hqUvagrcA1N9Zr7sflMewTMQky/xVd6J6EGYwxGYSqDor0vI+TWeLt3Bao/KrTKUwyCQoKIlu2bLRq1YpcuXLZHHzpWHwbbZ/iKuIC8B7wA/AHsDg5QhljTAzWAtUTerCILAY2AuVF5JiIPI6rsddcRPYBzd2vcd8ruApckyDjGuL+P+AfYKmq7kzUT2LSnNq1XYsxScU9cXpM679J6SyxCrsJF3dBLpuoMj06ceIE8+bN4+jRo+TOndsafOncbXv6RGQG8I6qjg1fp6ozRGQLkBPXhyBjjEkJ/YFVIrIZOBF5g6pOjutgVe0Wy6am0Veo6nGgTaTXt0yCbDKWV62jwyS92Ca+q5WiKW7n0j+Q2R8y53Y6iUliBw4c4IsvvuCBBx6gWLFiTscxKSCu4Z33AttF5DfgHeAzVQ1W1V+TP5oxxkQxCqiCq7DK1UjrFYiz0WeMMamBiIQPD/cUkW5ELRZVFtcE7anDpX/A9x6nU5hksH//frp06WINvgzkto0+VW0sImVxfcP+f8A0EVmIq/cvxcoMH/pxakpdyqSA6yFhTkcwSczHM0Vu7x0A3K+qf6fExYyJ7KGHXI/Lljmbw6QLr7gfMxP1C6sw4CQwNMUTxebyPvC92+kUJomoKhs3bqR06dK0bNnS6TgmhcX5SU1V96nqc7gq1g3GVTlvh4hsEJEeyR3QGGPcLuG6p86YFHf2rGsxJrFUtaSqlgS+CX/uXkqral1V/dbpjBEu7oac1uhLD8LCwli1ahV//fUXWbJkcTqOcUC8v55X1RBVXaKqzYBqQCFgQbIlM8aYqN4ExjgdwhhjkoKqtnc6Q5zObYGsRZxOYZLAypUrCQwMpHfv3uTMmdPpOMYB8Z2yAQARuR/XUM8uwFngxeQIZYwxMRgCFBeR4USbT09VyzkTyRhj4i/NTc5+5V/IUdbpFCYRgoOD8fb2pk6dOvj5+eHpeUcf/U06EuefvIjkBHoCTwAVgG+AzsD/kni+LGOMuZ1JTgcwxphEij45e+p15Qh4ZIVsxZ1OYhLo4sWLfPzxxzRp0oS777ZhuhldXFM2LAAewjUR+3vA+6p64nbHGGNMUhMRT1xfNj2kqsFO5zEZT9NbJvYw5s6lqcnZL+yA3NVAUqRQl0liJ0+eZPHixdSuXdsafAaIu6fPF3gEWG29esYYp6hqqIhUA0KdzmIyphftZgaTxETEF7ihqtdEJBPQCwgBPkkVn7ku74EcZZxOYRJox44dtGjRgnvusSk3jEtcUzZ0TKkgxhgTh4XAk8A0p4MYY0wS+AYYDmwCxgP9cH2xdQ+poWjVlaOQvZTTKcwd+vvvv8mdOzfNmjVzOopJZazP3hiTVtwHvCEi+0VknYisCV+cDmbSv9atXYsxSehuYKv7+aNAc6AukDqmw7p2DLIUdjqFiSdV5ZdffmHdunV4eaXu20WNM6yEjzEmrfjJvRiT4q5dczqBSYc8VPWmiBQHvFV1J4CI+DmcyyXokBVxSUN++ukndu3axeOPP25TMpgYWaPPGJMmqOoEpzMYY0wS+ltEXgCKAWsARKQgEORoKgBVuLgTfO1+sNQuNDQUEaFChQrUrFkTHx8fpyOZVOpO5+kToIBV8DTGOEFEigLdgaLAUVwFD446m8oYYxJkKDAbuAH0dq9rjrsB6KjQIBABb1+nk5jbCA4O5tNPP6VixYpUr17d6TgmlYvXPX0ikl1E3geuAfvd6zqKyLjkDGeMMeFEpB7wD9ABV2Xh9sA/IlLf0WDGGJMAqvqnqtZV1caqeti97iNV7e1wNLhxAbyswZeaXbx4kfnz51OgQAGqVavmdByTBsS3p+9NID+uG4zXuddtBiYDNuTKGJMS3gCGqer88BUi0huYAtRyKpTJGB54wOkEJj1KtaMXgk+CT36nU5jb2L59O1WqVKF27dq4BuIZc3vxbfQ9AFRQ1YsiogCqGiAihZIvmjHGRHE38GG0dQuBqSkfxWQ0I0Y4ncCkN+7RC6uBv4ADQFXgRRFpraobHA13PRB88jkawcTs0KFDZMqUiQYNGjgdxaQx8Z2yQXAN7fxvhUh2UsPNxsaYjOIUrmkbIrsPOO1AFmOMSazw0Qt1VLWnqtbFNRfpFIdzwY3z4J3L6RQmmp07d/LZZ59x8+ZNp6OYNCi+jb5fgNHR1g0FfkjaOMYYE6vpwCoReVlE+ojIRGCle70xyapRI9diTBKKbfRC+ZSPEk3wachsPX2pyR9//MGaNWvo2bMnJUuWdDqOSYPiO7xzOPC9iPQAsovI34AX0DTZkhljTCSq+raIXMBV5e4hXPe/PK2qix0NZowxCRM+emFLpHWpY/RC8Ckb3plKqCphYWEULVqUPn364OeXOqZxNGlPvBp9qnpURCoC7YASwGFgparadLXGmBTjbuBZI88Ykx6Ej154BzgIlAQGkBoK5F05AgVbOp0iwwsNDWX58uX4+/vTsGFDp+OYNC7e8/Sp6nXg82TMYowxtyUiPkBZIEfk9ar6ayLOWR5YEmlVKeAlVZ0WaZ9GwHLgX/eqL1R1YkKvaYwxqXr0QvApyOzvdIoMLTg4mKVLl5I5c2bq1KnjdByTDsSr0Sci82Lbpqr9ky6OMcbETETaAwtwzdEXmQIeCT2vqu4Bqriv4QEEAF/GsOsGVbXC/caYRBORMsC9wO+popEX3fUz4OHtdIoM7a+//sLf359WrVqRKVN8S3AYE7v49vR5RXtdCGiA9fwZY1LOm7iGPc1T1avJdI2mwIHwiZKNCde5s9MJTHohIg/iGl3gAdwQkQdVdZXDsaIKvWrz9DnkzJkzXLlyhfvvvx/A5uAzSSa+9/T1ib5ORDoBLZI8kTHGxCx/5CGXyaQrsd8zWFtEtgPHgRGqujP6DiLSH+gPUKxYsWQLaVLe4MFOJzDpyAvAGGAOrikaxgCpq9EXfAI8szudIsM5cuQIS5cupUWLFtbYM0kuMf3FXwFdkiqIMcbEYY2I1Equk4uIN9Ae+CyGzduA4qpaGZiJ6/ffLVR1nqpWV9XqefPmTa6oxgFXr7oWY5JASeBNVb0CvAWUSchJRKSViOwRkf0iMuo2+90vIjdF5OH4n9wTvK1KZErat28fS5YsoVOnTlSqVMnpOCYdinchlxi0JtqE7cYYk4wOAStEZAlwIvIGVZ2cBOdvDWxT1VPRN6jqpUjPV4nIHBHxV9XAJLiuSQPatHE9rl/vaAyTPnioahiAqoa4v3C6I+77j2cDzYFjwGYRWaGqu2KzBMwJAAAgAElEQVTY73Xgf3d0gZCL4JHtTmOZBAoLCyNPnjz06NGDggULOh3HpFPxLeSyD1exhHDZgHzAU8kRyhhjYlAN2AlUdC/hFEiKRl83YhnaKSIFgFOqqiJSA9coibNJcE1jTMbjLSJjIr32ifY6Pl9k1QD2q+pBABH5FOgA7Iq231BgGXB/vNO52qNWyCUFqCrfffcdISEhtG7d2uk4Jp2Lb0/fpGivg4A/wn/ZGGNMclPVxsl1bhHJiusb8wGR1g10X3cu8DAwSERCcY1w6KqqGtO5jDEmDr/h+n0T7vdor+PzRVZhXFM8hDsG1Iy8g4gUBjoBTYij0Rf5fuQSxYvYdA0p4ObNm6xYsYJz587RrVs3p+OYDCDORp+IeAL5gRmqGpz8kYwxJmW5q4HmibZubqTns4BZyR5k/PjEbTfGpHqq2igJThNTlY/oX0RNA0aq6s24ioKo6jxgHkD1qhUV76xJENHczq5du7h+/Tq9evXCyyt6kXxjkl6chVxUNRQYYw0+Y0xKE5EfRaRhHPs0FJH1KRTJGGNSg2NA0Uivi+CqLBxZdeBTETmEa7TCHBHpGOeZw26AR+Ykimmiu3z5Mv/++y8VK1akc+fO1uAzKSa+wzt/EJGGqvpjsqYxxpioJuP6oOIFrMN1v8olICdQAde8eqHAcMcSmgyhd2+nExgTxWagrIiUBAJwTTfTPfIOqloy/LmIfAisVNUYKw9HERYKvvckaVjjEhgYyKJFi6hWrRolS5a0aRlMiopvo+8QsFxEPnc/DwvfkERV84wx5haq+j/gHhFpiatIQQ8gF3Ae+AMY5t7HmGRljT6TmqhqqIg8iasqpwcwX1V3RrsXOYEnvwFZCidNUBMhICCAxYsX07RpU6pWrep0HJMB3bbRJyKXVDUnUAXXB6zS7iVcUlXNM8aYWLkbdta4M44JdE/O4W/1LUwqoaqriDape2yNPVXtHe8Th4WCj80zmpRUlezZs9OpUydKly4d9wHGJIO4evoEkrdqnjHGGJPaPeye1trm6TNJTVxj/Aqo6ok4d04JehO8cjqdIt3YsmULx44do2PHjvj6+jodx2RgcRVysZLkxhhjjDFJTESyi8j7uKaB2e9e11FExjkaTMPA0xp9iaWqfP/992zcuJEGDRo4HceYOHv6fERk/u12UNW+SZjHGGOMMSYjeBPXlFh1cRWqAleBlsnABKdCwU3wtCkbEuvgwYMcPHiQvn37ki1bNqfjGBOvQi43kz2FMcYYY0zG8gBQQVUviogCqGqAiBRyNFVYKGSyaQQS6saNGxw/fpzSpUtTokQJPDw8nI5kDBB3oy9YVZ9IkSTGGHMH3KXKb6rqEaezGGNMAgiuoZ3/rRDJDgQ5EyecgpefsxHSqKCgID755BMKFy5sDT6T6sQ5ObsxxqQGIjJfROq6n3fDdQ/MQRHpfvsjjUm8QYNcizFJ6BdgdLR1Q4EfHMgSYfuBsmQqUJe8eWHcOAhyuAmaVpw7d4758+dTrlw52rRp43QcY24Rr+qdxhiTCrQGhrifDwceAi4CM4FPnAplMoYuXZxOYNKh4cD3ItIDyC4ifwNeQFMnQ4WGeQJCYCC88QYsWwa//QbZszuZKnVTVby8vGjYsCGVK1d2Oo4xMbptT5+q5kipIMYYE4esqnpNRHLhmi90uar+ABR1OJfJAI4edS3GJBVVPQpUxNXbNwaYCFRV1QBHg0USHAwHDsCUKU4nSb327t3L559/To4cOazBZ1K1+BRyMcaY1CBARBoCdwMbVFVFJCcQ6nAukwH07Ol6tHn6TFJS1evA507nuJ3gYHj7bZjgYD3R1Grbtm388MMPdLGhACYNsEZfEvpi6WJWfLmUkyeOA1CyVBl69e1P7XoNCQ0N4d23Z/L7rxs4fuwYWbNl477qNRjw5DPkL1AQgEsXLzJ/3my2/L6RkyeP4+vrR536Dek3cBi+fv/dVH308CHenvkWf/+5jRshNyhZqgx9nhhMzTr1HPm506ttWzez6KMP2L1rJ2fOnOalCZN5oEOniO0TXhzNN19/FeWYivdWYv7CJQAcDwigY9tmMZ576NMj6Nn7cY4HBPD+u3PYunkTZwPPkMc/L81btubx/oPx8fFJvh8ubZoIrAVuAOE3TDQD/nQskTHGJJCIzIttm6r2T8kscTl71ukEqc+JEyf4+eef6d27N3ny5HE6jjFxskZfEsqbPz8DnxxOkWLF0bAwVn+znDEjnuK9hUvIX7AQ+3bvomef/pQtdxdBV4KYM20KI4YN4INPvsDT05PAM6c5c/oUA4cOp0Sp0gSePsVbr09iwgvP8dasdyOuM3L4EAoVKsLUOe/hkyUry5ctYcyIoXy0dDmFixRz8B1IX65dvUrp0mVp80AHxr84KsZ9atSszfhXXo947eX1X5nr/AUKsGrdT1H2X//9Oqa8+jJNmrcE4PChg4TdDGPk2HEUK1acfw8e4NWXx3HxwgXGvDQxGX6qtEtVPxWR5e7n4RXvfgZ+dS6VMcYkWPR5EQoBDUiFPX/WpvlPWFgYAQEBFC1alEGDBkX5f9+Y1MwafUmofsMmUV4/Mfgpvlq2hB1/b6d02fK8Nfu9KNtHjB5Hry4dOHzoIKXLlKNUmbK8MmV6xPYiRYsx6KlnGfXMEK4EBZEte3YuXDjPsSOHGTF6HGXK3QXAgCef4bPFC9m3Z7c1+pJQ3foNqVu/IQATXxoT4z5e3t74++eNcZuHh8ct29Z/t5YaNWtTuHARAGrXrU/tuvUjthcuUpQ+/QYwd84Ma/TF7AZQU0SKquoSXKXN1eFMxhhzx1S1T/R1ItIJaOFAnFj5+Fjl2nA3btxg2bJlAHTt2tUafCZNsSkbksnNmzf5bs0qrl29SsVKVWLc58oVVx3kHDlyxnqeq1eC8PL2JrN7qJ+vrx/FS5ZizaoVXL16lZs3b/L1l5+TNWs2KlaumvQ/iLmt7X9so2XjujzUvhWvTHiRc+diHwMTEHCMzZt+o+NDnW97zitXrpAzp29SR03zRKQ0sANYBbzvXt0CeDfWg4wxJm35Ckg1N4j5+EDp0vDcc04ncd6VK1f46KOPyJIlC507d0bECtybtMV6+pLYgf17Gdz3UW7cuEGWLFl5Zcp0Spcpd8t+ISEhzJ42hTr1G5Evf4EYz3X58iXemzuLdh0fwtPT9UclIrw1613GPvcUrRvVJFOmTOTI6csb09+OtcfJJI/adevRuGlzChUuwonjAbw9ezqDn+jNR4uX4e3tfcv+y5d9hp9fLho2ahLD2VxOnjjOxx/Np/fjA5Izelo1E/gUeBkIb12vB6bHdoAxSeXZZ51OYDKI1kSbsD2leWYKJQzXkM5Bg1wNPpuuwfX565577qFWrVrW4DNpkjX6klix4iV5f9Eygi5f4sfv1zJ5/Fimz/2AUmXKRuwTGhrKpJdGEXT5Mq++OSvG81y7dpXRw58kb958DBz636cNVeWt1yfh6+vHrHcX4J3Zh2++WsaLI59h3oJPyZsvf7L/jMalRau2Ec/LlC3HXXffQ/s2Tfllw3oaN406Oic0NJSVX39J2/Yd8YxlOMjZs4EMG/wENWvVoXuPx5I1expVA2ivqmEiogCqekFE/OI4zphEa9fO6QQmvRGRfUQdnp4NyAc85Uwil8ol/2HLficTpC7Hjx9nw4YNdO7cmdq1azsdx5gEs0ZfEvPy8qJIUdd9dXdVqMjuXTtZuvgjRr34MuD68D/xhec5uH8f0+d+EKUqZ7irV6/y/NOuAfSvTZ1D5syZI7Zt2/w7v25Yz8rvfokYFlp+VAU2b9rIqq+/4jHrIXJM3nz5yJcvP0eOHL5l24affiDwzBk6PPhwjMcGBp5hSP8+lCpdlvGTXrdvEWN2CfADAsNXiEgh4JRjiUyGsWeP67F8eWdzmHRlUrTXQcAfqnrQiTARxO78Cbdv3z6++uor2rVrZ/8vmzTPGn3JLEzDCLlxA4DQ0BDGj3mOfw/sZ/o7H5DH3/+W/a9eucJzTw1EVfm/Ge+QNWvWKNuDg4MByBTtl3ImyYSGhSXTT2Hi48L585w5fTrGYbbLl33GfdXup3jxkrdsCzxzmkFP9KZU6TJMeu3/Iobymlt8AcwXkcEAIpIHmIZryGeiiMgh4DJwEwhV1erRtguuYaRtgKtAb1XdltjrmrRjgPv7NJunzyQFEfEE8gMzVDXY6TxRWW0sgAsXLrBixQq6du1K0aJFnY5jTKLZp8skNHfmVGrXa0C+/AW4evUK61Z/w59bN/P61DmEhoby0qhn2b1rB6++NQtBOBvo6rDInj07mX18uHrlCs8O7c+VoCBe+b8ZXLt2jWvXXEP7c/r64uXlxT2VKpMzpy+vTnyB3v0GkjmzD19/9TnHA45R211p0iSNq1evcOzIEcDVeD958jh7d/9DTl9fcvr68u7c2TRu2hx//3ycOB7A7JlvkTt3bho1aR7lPCdPHOe3jb8w/uXXbrnGmdOnGdivF3nz5mP4c6O5cOF8xLZcuXLj4eGRvD9k2vIirgIuR9yvTwOfAJOT6PyNVTUwlm2tgbLupSbwtvvRGGPumKqGisgYVX3D6Sy3ytg9WqrKyZMnKViwIEOGDLE5c026YY2+JHTubCCTXhrFubOBZMueg9JlyjFl+lxq1K7LieMB/Pzj9wA80TNq9cbRL02idbuO7Nm9k51/bwfg0YfaRtln+tz5VK1WAz+/XEyZMZd3357B04MfJzQ0lOIlSjH5/6ZT/q4KKfODZhD/7NzJoCf+u7du3tuzmPf2LNq268jIsePYv28vq75ezuXLl/HP60+16jV59Y2pZMuWLcp5Vny5jOzZc9C42a1VuH/f+AtHjxzm6JHDtGsVtcDLV9+so1Dhwsnzw6VB7rn5uovIMKAEcFhVz6TQ5TsAH6mqAr+JiJ+IFFTVEyl0fWNM+vODiDRU1R+dDhKFZNyPhmFhYaxatYrjx4/Tr18/a/CZdEVcn2FSt1OXQlJ/SBNvPl7We5Xe+GbJlKa/GhaRf4HzuMY1vaOq86JtXwm8pqo/u19/B4xU1S3R9usP9AcoVqxYtcOHb72/k/HjEx40MceaRGnUyPVowzvTDxHZGn0odwpffyrQB9dk7IeAiHs0VDWpRjDcserlc+qWPZecurxjQkJCWLZsGSEhIXTu3DlKPQVjUovE/N7KuF/nGGNSPRFZSzxuMFHVxE5mXFdVj4tIPmCtiOxW1Z8iR4npsjHkmAfMA6hevbp9WWWMuYWIXFLVnEAV4A+gtHsJpyTdsPUESNPf4SXYzZs3yZcvHw0bNrRbK0y6ZI0+Y0xq9nNKXERVj7sfT4vIl7imh4jc6DsGRL6TvwhwPCWymdThhRecTmDSEQFQ1cZOB4lZxmr0XbhwgXXr1tGxY0eaNIl9Hl1j0jpHG30i0kdVP4hlW8QwqSnT5tCzT78UzWaMcZ6qTkjua4hINiCTql52P28BTIy22wrgSRH5FFcBl4t2P1/G0qyZ0wlMOpK6RwFkoDbfiRMnWLx4MfXq1bPK2Sbdc/pv+AQgxkZf5GFSdk+fMQZARLIDD+DqaTsGfKOqlxN52vzAl+45mDyBT1R1tYgMBFDVucAqXNM17Mc1ZUOfRF7TpDF//ul6rFLF2RwmXfARkfm320FV+6ZUmFtljHn6rl69yieffELr1q2pUMEK4Zn0L9kbfSLyV2ybcH3YSlF/bN3EUwP7smLtBvz8cqX05VOVyePHcvHieV6fOsfpKAbYunkTg554jDU//Ipfrtj/bg58vBely5TludEvpmA654lIdVyNr2u4pm0oBswQkTbRC6rcCfdEyJVjWD830nMFhiT0Gibte/pp16MVcjFJ5KbTAWKX/rv6AgMD8ff3Z8CAAWTPnt3pOMakiJTo6csPtMRVGS8yAX5NyAknjx/L6m+W37L+/Y8/p2z5uxJyyiQ1bEBv/ty2hRcmvEqLNu0i1n/79VdMm/IK//tpc4rmia2hO2zEKFJ79dYaVe6+7fa27Toy7uVXUyTL8YAAOrb9b4xXjhw5KV22LAMHD+O+6jUSff5KVaqwat1P+Pr5AbBy+ZdMeW0SP27cGmW/19+agaenV6KvlwbNAd5U1dfDV4jI87jmzLvfsVTGGHNnglX1CadDxErSb6NPVfnll1/YunUrgwYNsgafyVBSotG3Esiuqn9G3yAi6xN60uo1ajF2QtTJrsM/LKcG3pkz897cmTRq1hJvb2+n48Qoe/YcTkeI06p1/9XS+Pmn9Uye+FKUdT6Zo86hExoSgqdX8jaIps95l7LlynP+3DnmzJzK008OZPGyFRQuXCRR5/Xy8sbfP2+c+/n6pp6/5ynsbuDNaOvewjVpuzHGmCSRPht9YWFhrF69miNHjtCnT59U+9nMmOSS7AO3VfXx8LmtYtjWPaHn9fL2Jo+/f5TF09OTJYsW0LtbJ1rUv58H2zTh9Ukvcfly7PPNBAVdZtJLo2jfogHN6t5Hlw6tWPrJwijbp7wynvYtGtCyYQ2G9u/N7l074szXpFkrbly/zpefLb7tfn9v/4Oh/XvTvF51HmzThDdfm8iVoKCI7deuXeWVcaNp2eB+OrRswMcfvMvIZwYzefzYiH3WrPqa/r260LJhDdq3aMBLo4Zz5vQpAE4cD+Cpga5bA9o3r0+D+ytGHDt5/FhGPjMYgOVfLKVDywaEhoZGyTfxhecZ/ezQiNe//LSefj0706zufXTu0JJ350wnJCQkYvuP36+ld7dONKtXjbZN6zC0f2/OnQ2M8/2Kjb9/3oglR46cUdbduH6DJvVr8L9vv2HQE72pX7MKXyxbysrlX9KwdrUo59m6eRM1qtzNhfP/dTj/9ecfDHi8J/VrVaVt84a89sp4giK997Hx9fXD3z8vZcuVZ/QLEwgOvsbvG38BYNvWzfTp0YV6NSrTqkk93pryKiEhNyKO3bZ1M317dqFh7Wo0rnc/fXp04cD+vbdk3Lp5ExPHjeHatavUqHI3Narczby3ZwGu4Z1TXn0ZgNkz3qJXt4duyfh4r268+fp/Fb+//uoLujz4APVqVOah9q34ZOGHhIVFTAnFF58v4aH2rahXozItGtdh6KB+t/xdSAX+BCpGW3eve70xxqQVqbxVlcrjJVD4/2m9e/cmZ86cDqcxJuWlu7t1RTIxdPgoFiz5ipdefp1/dv7N9CmxT3fz3tszObh/H69Nnc3Cz75m1EsTyZsvH+AaBjDy6cGcOXOK16bO5v2PP6dy1Wo8PfhxAgPP3DZHlqxZeazfIBZ+MC/WRueB/XsZMbQ/dRs0Yv4ny5j0xjT2793Day//13Exe9oU/ty2hUlTpjNtznz279vDX39si3KekNAQ+gwYwgeLlvHa1NlcvHCeCS88D0C+/AV4+fWpAHy0ZDlffrueYSNG3ZKlSbOWBF2+zNZNv0Wsu3btKj//+AMtWj8AwKaNv/DySyN58JFuLFjyFaNefJn1361l3uxpAJwNDGTC2Odo1bYDC5euYOY7C2jZ5oHbvk9JYc6Mt3i4czc+/WIlDRs3jdcx+/ftZeigfjRo2IRFS77k9bdmsHfPbiZFakzHh08WV09jaGgop0+d4ukhAyh3190s/PQLxo5/mTWrVzF7xtSIfZ57+kkqV63GoqVf8sHCJXTp3pNMmW6dD6hSlSoMf240Pj5ZWLXuJ1at+4kej91aO6R12/bs/mcXh/49GLEuIOAYf//1J63buoYWf7VsKXNmTaX/oKEs+fIbnn52JB99+D6fL3V9IbFr5w6mvPoyTwwYwmdfrWLW3PnUrlPvjt6HFLIGWCki40Wkj4hMwFVVc42IdA9fHM5ojDG3paqpe5hNOhveee3aNZYvX05YWBht2rTBx8cn7oOMSYecrt6ZYJs2/kLLBv/dxlOpSjWmzJhL5+49I9YVLFSYQUOfZcyIoYwZP5lMmW5t4548cZyy5e+mwj33RhwTbtuWTezfu5sVazaQ2f1Lot+gofy6YT1rVn1N9163L67VrtPDfPbpQhZ9+D4Dhz5zy/ZPF35A4+at6Nqjd8S64SNf5PEeD3P+3Fky+2Rh1YovGTthMvfXrAPAyBcn8lDbqLXD27Z/MOJ5oSJFGT7qRXo+0p7Tp06SL38Bcvr6AuCXO3esxWty5PSlVt36rF29kpruD/wbfvgODw8P6tRvBMBHH8yjW48+tGnfCYDCRYoxcOgzTHppFIOfGkFg4GlCQ0Np1LQFBQoWAqBUmbK3fY+SQuduPWjavOUdHbNwwfs0a9mKR3v915AaNWYcPbo+yLlzZ8mdO0+c57h27SqzZ0zFw8OD+6rdz+dLF+OfNy8jx7xEpkyZKFmqNE8OG86rk8YxcPAwrt+4zuXLl6jfoBFFihYDoETJUjGe28vLm+zZcyAitx3yWap0GcqVv5vVq75m4JCnAFi96muKFS9BhYquv9PvvzuXoU+PiHiPChcuwmN9+rFs6WI6d32UUyeP45MlC/UbNSFbtmwUBMqlgntjY9AXCAEei7Qu1L0+nAKfpGQokzFMdnCqbGNMwly8eJGPP/6YMmXKkDlzZqfjGOOoNNvoq1S1Gs+NGR/xOvwf89bNv7Pow3c5fOhfgoIuE3YzjJCQEM6dDcQ/b75bztPxoS68NGo4e/fsonqN2tSt34gq1VyNyb27dxIcHEz7FvWjHHPjxg0Cjh2NM6OnpydPDBrG5PFjebBzt1u27/lnFwHHjvDD2tUR68LrqgQcO4qPjw+hoaHcXeHeiO1ZsmSlVOkyUc+zexcfvvs2+/fu5tKlixEnOXXyBPnyF4gzZ7jmrdvx6oSxBAdfw8cnC2tXf0PDps0j3tu9/+xi986/+eSj9yOOCQtTrl8P5uzZQMqULU/1GrV4rGtH7q9Zh+o1atGoaQv8cuWOd4aEuLvCPXd8zO5dOzl29Ajr/hf5vXe9b8eOHrlto2/A4z3JJJkIDr6Gv39eXpo4mTJlyzHv7ZncW6lylC8XKle9j5CQEI4ePULZcuV5oH0nhg1+gvtr1KJ6zdo0a96S/AUK3nH+yFq3bcfnSxdHNPr+t2plRC/f+XPnOHXyBK9OGs/rr/w39dzNm6ERP2+NWnUpWLAQHds2o1btetSsXZfGTZuTLVu2ROVKaqpa0ukMJuOqU8fpBMakkFRe4C2+QkJC+PDDD6lRowa1a9d2Oo4xjkuzjT4fH5+I3pJwJ08cZ+Qzg2nX8SH6DngSX18/9u7ZxYSxz0e57yyyWnXrs/TrNfz+6wa2bvqdkc8MplHTloweN4mwMCVX7jzMevejW46L7wfixs1a8unHHzJ/3mwqV4l6n1mYhtG2w0N07t7rluPy5s3HkcOHXC9uM9Ti2rWrjBg6wF3Y5lVy5c7NxQsXePKJXoSGxvwzx6ZOvYZ4eHjy848/UO3+mmzZ9BtvzpoXJW/vfoNo1OzWXjU/v1x4eHjw5qx32fn3djb//ivfrPiCebOnM+OdDyhTLvl6jnyyZI3yWjLJLVVJo78XqkqHTg/TrcdjRJc33+1nEnl58hTKlC1H9hw5ovScqmqsf1buOeB4aeJkuj7ai42/bmDD+u+ZO2sab0ydlajhlC1bt2XmtP/jr+1/4O3tzaF/D9LKXTU2TF337Y0aO45KlavGeHy2bNn4aPEy/ti2hU2//cqC+fN4e+ZUPlz0WcRQZ2Myul/dtaat8WfSvUxp9qNhhIsXL+Lr68tjjz2GXyoq8meMk9L+v+xIdv+zk9CQEJ58ZiQeHq77pH79+cc4j/Pzy0XLNu1p2aY9NevUY+ILz/Ps6Jcod9fdnD93lkwiFCpSNMG5Bg0dzjND+pEzp2+U9eXKV+DQwf23NF7DFS5aDE9PT/7Z+TeF3JUhg4OvcfDAfgoVduU5cuhfLl44zxODn4rY58fv10Y5T3h5/7Cbt58WyNvbm0ZNmrN29UouXjhP7jx5qHJf9Uh57+bw4X9jzQuuxk3FSlWoWKkKvfsNoleXDny/dnWyNvqiy5UrN8HB1wgKCooox7x3z+4o+5S/qwIHD+ynaLHid3z+fPkLxPgelCxVhu/WfEtYWFhEb9/2P7bh5eVFkUh/f8qVv4ty5e/isT5P8NSQ/nyz4qsYG32eXl6EhcU9lZN/3nxUv78m/1u1Ei9vbypVrkph9/Xy5PEnX778BBw9Stt2HWM9h6enJ/fXqMX9NWrRf9CTtGxcj59/Wk+nhzvHef2UIiIFgPG4pmeIck+MqpZzIpPJOMaMcT3aPH0mtRCRVsB0wAN4T1Vfi7b9UWCk+2UQMEhVt8d95rRd7mHHjh2sXr2aQYMGWYPPmEjSVaOvaNFihIWF8dnihTRo3IxdO/7is8ULb3vM+3NnUe6uuylRqgw3b4by0w/rKFS4CN7e3lSvUZt7K1dl9IhhDBo6nGIlSnLubCCbNv5MtRq1qVy12m3PHa5KtfupUbsuX3y2GI9IQ/8efawvA/s8yv+9OoH2D3Yma9ZsHDl0kF82/MhzY8aRNWtW2rTvxDuzpuLnl4s8/nn5aP47aFhYRM9R/gIF8fb25ouli3nwka4cPnSQ9+fOinL9AgULISJs/OUn6tZvhHdmH7Jmjdo7Fq5F6wd4ZsgTnAgIoFmrtlGGKvbuN4iRzwyhQIFCNG7WEg9PD/49sJ9/dv7NoGHPsvPv7WzZ9Bs1atUhdx5/9u75h9OnTlKiZOl4vU9J5Z57K5ElS1bmzHiLbj0eY9/ePRFFS8L16tOPvr268uqk8Tz4sOu9P3ToID//uJ7RL05I0HUf7tyNTxd9xOuTJ9K1e08Cjh1l1oy3eKTro/hkyUJAwDG+/HwJDRo2IW++fAQEHGP/3j082LlrjOcrVKgw169f5/eNv1D+rgr4+PjgkyVLjPu2atueGVPfwMvTiz5PDIyyrd/AIbz5+itkz5GDuvUbEhoawu5/dnHm9Gl6P96fDT/9QMDRo1StVp2cOX3ZunkTV69eoUSpmO83dNAi9+N7wHH/0TIAACAASURBVFUngxhjjJNExAOYDTQHjgGbRWSFqu6KtNu/QENVPS8irYF5QM14nDwZEic/VWXjxo38/vvv9OzZM9XdomCM09JVo6902fIMe3YUn3w0n/fmzqTivVUY/NQIxo8ZEesxXt5evDtnBieOB+Cd2ZsKFSvz6luuRpOI8Ma0t3n37RlMmTye8+fOkit3Hu6tXJWWbdvfUbYBQ56h76MP4RHpRuLSZcszc96HvPf2TIYN6E3YzTAKFi5Cg0b/VaAc/NRzBF+7xuhnh5IlaxYe6daLc2fP4p3ZNb+MX67cjB73Cu/Omc5Xny+mVJlyPPnM84wYNiDiHHnz5adv/yG8O2cGb0waR8s27Rkz/pUYc1a+rzp58+Xj0L8HGDd5SpRtNWrX5fVps/no/Xf49OMP8fD0oGix4rR6wNWDlC17dnZs/4Mvli4i6PJl8uUvwGOPD4wyQX1K8PX1Y+LkN5gxdQpfL/+CKvdVZ+CQYYwbOzJin7LlyvPO+wuZO3s6Ax/vxc2bYRQuUoRGTZrd5sy3ly9/fqbNfoeZU/+PHl06kSNHTlq0bstgdxEfHx8fjhw+xOjnnubChfPkzuNPyzYP8FjvfjGer1KVqjz4SBdeGD2Cixcu0G/AEPoPejLGfZs0a84bkycSFBpEsxatomzr+OAjZMmSlY8XvM+cmVPJnNmHUqXL8EhXV6HLHDly8uMP3/HevDlcDw6mcJGijH3pZapG6uVNJaoD+VU12OkgxhjjsBrAflU9CCAinwIdgIhGn6r+Gmn/34B4TiabNu/pCwsL48yZM/Tt2xdfX9+4DzD/396dx0dR3g8c/3wT0IAgl4IHIpdABCFqVOQyoIBQ8Kj4Q7CcUkXFs971QLCWoi1WKVoryOGBBwparVpQEAXFqAFBbAQMiKhgJOGGhHx/fzyTsNlsNkuy2SP5vl+vfWVnZ+aZ70x2np3nmGdMNSP+9z7Fop935MV+kBFy4MAB/m9gb64YNqrYqJ/xJKlmyUcUmPhWr1ZCpVcNi8gK4GJV/bGytxUOqampmp6eXnLG+PHlT7Qi65oKSUtzf617Z9UhIp+raszVboVCRAYBF6rqGG96GHCOqgasGRSR24B2hcsHmH81cDVA25MbnvlNVnblBF4J8vPzWbRoEd26dbPWPVPlVSTfqlItfVVR5v/WsvG7DSS3P409e3bzwqzp7Nmzh169Lyx7ZWOqlt8DT4rIbOAn3xl+NdrGGFPVBapoC1hBLiI9gauAUkcMU9Wncd0/ST2tedxUtO/bt4+5c+dy1FFH2SMZjCmDFfriwMsvzGLTxiwSE2twShvXJfRwHsVgTBWRDJwP+PetVtxABsZUmscei3YExhSzGfAdYa4psMV/IRHpiLsPup+qhth8Fx/39BUUFDB79mxOOukk+vbtG/BZzMaYQ6zQF+PatE3mX7NfjnYYxsSCR4DbgNmqujfawZjqJSUl2hEYU8xnwCki0gL4AbgCGOq7gIg0A14DhqlqZuhJx36hb/fu3Rx11FFceumlHHPMMUWD2xljSmeFPmNMvKijqv+MdhCmelq40P29oPxjPRkTNqqaLyLjgHdxPR1mqOoaERnrzX8KuB9oBEzzCkX5Id0LFOMFqKysLF599VVGjx7NscceG7Z08/Ly2Lx5M/v22VhhJvqSkpJo2rQpNWvWDFuaVugzxsSL10TkQlV9J9qBmOrnoYfcXyv0mVihqm8Db/t99pTP+zFA4OGh49SaNWt4++23ueyyy2jYsGFY0968eTN169alefPm1nJookpVyc7OZvPmzbRo0SJs6VqhzxgTL2oC80TkfaDYCJ6qenV0QjLGmComRkd1V1UyMzMZNmwYxx0X/nEN9u3bZwU+ExNEhEaNGrFt27awpmuFPmNMvDgIFN7gGr7+DsYYYw6R2BoQRVVZunQpKSkpXHrppZW6LSvwmVhRGd9FK/QZY+KCqo6KdgzGGFP1xU7BJz8/nwULFpCbm8tZZ50V7XCMiWuxVZ1jjDFlEJFaInKSiDQrfEU7JmOMqTJipMynqrzyyivk5+czbNgwatWqFe2QKl1iYiIpKSl06NCBgQMHkpOTUzRvzZo19OrVizZt2nDKKacwceJE1Kcr7n/+8x9SU1NJTk6mXbt23HbbbdHYhaC+/PJLxoyJ3dtM9+/fz+DBg2ndujXnnHMOWVlZAZd76aWX6NixI+3bt+eOO+4Iaf077riD9u3bk5yczI033lj0v7viiiv49ttvK3O3ilihzxgTF0SkpYgsA3YBWcB3Pq+KpHuSiHwgImtFZI2I3BRgmTQRyRWRDO91f0W2aeLPP//pXsaYyrdv3z5EhLS0NC6//PKwjmAYy2rVqkVGRgarV6+mYcOG/OMf/wBg7969XHTRRdx1111kZmaycuVKli1bxrRp0wBYvXo148aN47nnnmPt2rWsXr2ali1bhjW2/Pz8Cqfx8MMPc8MNN0R0m4dj+vTpNGjQgHXr1nHLLbdw5513llgmOzub22+/nUWLFrFmzRp+/vlnFi1aFHT9ZcuW8fHHH7Nq1SpWr17NZ599xpIlSwC49tprmTx5ckT2z7p3GmPixVTge+Bq4COgKzABeLOC6eYDf1DVL0SkLvC5iPxXVb/2W26pqg6o4LZCsjhrceAZI9MASGueVnLe+PGVFI0BaNs22hEYUz1s27aN559/nssvv5wTTzwx2uFEzbnnnsuqVasAeOGFF+jatSt9+vQBoHbt2kydOpW0tDSuv/56Jk+ezB//+EfatWsHQI0aNbjuuutKpLlr1y5uuOEG0tPTEREeeOABLrvsMurUqcOuXbsAePXVV/n3v//NzJkzGTlyJA0bNuTLL78kJSWF119/nYyMDOrXrw9A69at+fjjj0lISGDs2LFs2rQJgMcee4yuXbsW2/bOnTtZtWoVnTp1AmDFihXcfPPN7N27l1q1avHss8/Stm1bZs6cyVtvvcW+ffvYvXs3b775JjfccANfffUV+fn5jB8/nosvvpisrCyGDRvG7t27AZg6dSpdunSp0DFfsGAB473f0kGDBjFu3DhUtdj9dRs2bKBNmzZFjwu54IILmDdvHueff37Q9fft28eBAwdQVfLy8mjSpAkA3bt3Z+TIkeTn51OjRuUWy6zQZ4yJF+cAzVV1p4jgPZPqGmAJMLO8iarqj3ijgXpprwVOBPwLfaYae9OrWhg4MLpxGFOVbdq0iZdffpnevXtHv8D3QiX0cx0a2sioBw8eZNGiRVx11VWA69p55plnFlumVatW7Nq1ix07drB69Wr+8Ic/lJnuxIkTqVevHl999RUA27dvL3OdzMxMFi5cSGJiIgUFBbz++uuMGjWKTz/9lObNm9OkSROGDh3KLbfcQrdu3di0aRN9+/Zl7dq1xdJJT0+nQ4cORdPt2rXjww8/pEaNGixcuJB77rmHefPmAbB8+XJWrVpFw4YNueeee+jVqxczZswgJyeHs88+mwsuuIDGjRvz3//+l6SkJL799luGDBlCenp6ifi7d+/Ozp07S3z+6KOPcoHfM3h++OEHTjrpJMAVnOvVq0d2djbHHHNM0TKtW7fmm2++ISsri6ZNmzJ//nwOHDgQdP1zzz2Xnj17cvzxx6OqjBs3juTkZAASEhJo3bo1K1euLPE/Djcr9Blj4kUBsNd7v0tE6gO/AmG7p09EmgOnA58GmH2uiKwEtgC3qeqaAOtfjWuJpFkzu9WwKvnrX91fK/QZU3m++OILLrnkElq3bh3tUEIuoIXT3r17SUlJISsrizPPPJPevXsDlGht8nU4ozwuXLiQuXPnFk03aNCgzHUuv/xyEhMTARg8eDATJkxg1KhRzJ07l8GDBxel+/XXh+pJd+zYwc6dO6lbt27RZz/++GNR6xhAbm4uI0aM4Ntvv0VEyMvLK5rXu3fvoucwvvfee7zxxhs8+uijgOv6u2nTJk444QTGjRtHRkYGiYmJZGZmBox/6dKlZe5jIQ3wuBL/49ugQQOefPJJBg8eTEJCAl26dGHDhg1B11+3bh1r165l8+bNRfv34Ycf0qNHDwAaN27Mli1bKr3QZ/f0GWPixRpcl05whbIpwONU8J6+QiJSB5gH3KyqO/xmfwGcrKqdgCeA+YHSUNWnVTVVVVN9f9yMMSZ+RH4kly+++IKcnJzYKfBFSeE9fRs3buTAgQNF9/S1b9++RCvWhg0bqFOnDnXr1qV9+/Z8/vnnZaZfWuHR97N9+/YVm3fUUUcVvT/33HNZt24d27ZtY/78+fz2t78FoKCggOXLl5ORkUFGRgY//PBDsQJf4b75pn3ffffRs2dPVq9ezZtvvllsnu82VZV58+YVpb1p0yaSk5OZMmUKTZo0YeXKlaSnpxe1tvnr3r07KSkpJV4LFy4ssWzTpk35/vvvAXc/YW5ublHh09fAgQP59NNPWb58OW3btuWUU04Juv7rr79O586dqVOnDnXq1KFfv3588sknxY55JAYqskKfMSZe3Ihr2QO4HWgKpALXVDRhEamJK/A9r6qv+c9X1R2qust7/zZQU0SO8V8uUhZnLS7xGr94fNHLGGPigaqycOFCli1bFrCVpLqqV68ejz/+OI8++ih5eXlceeWVfPTRR0UFlb1793LjjTcWjRx5++238/DDDxe1dhUUFPC3v/2tRLp9+vRh6tSpRdOF3TubNGnC2rVri7pvlkZEuPTSS7n11ltJTk6mUaNGAdPNyMgosW5ycjLr1q0rms7NzS3qwjtz5sxSt9m3b1+eeOKJou/Hl19+WbT+8ccfT0JCAnPmzOHgwYMB11+6dGlRgdH35d+1E+Ciiy5i1qxZgLu3sVevXgELyVu3bgXc8Zs2bVrRiKSlrd+sWTOWLFlCfn4+eXl5LFmypKh7J7gutO3bty/1GISLFfqMMXFBVVep6lfe+w2q2ltVO6vq8oqkKy5Hnw6sVdWSv5JumeO85RCRs3F5Z3ZFtmuMMdXdW2+9xcaNGxk9enRIXQ2rk9NPP51OnToxd+5catWqxYIFC3jooYdo27Ytp512GmeddRbjxo0DoGPHjjz22GMMGTKE5ORkOnTowI8//lgizXvvvZft27fToUMHOnXqxAcffADApEmTGDBgAL169eL4448PGtfgwYN57rnnirp2Ajz++OOkp6fTsWNHTj31VJ566qkS67Vr147c3Nyi++vuuOMO7r77brp27VpqgQ1ci2BeXh4dO3akQ4cO3HfffQBcd911zJo1i86dO5OZmVmsdbC8rrrqKrKzs2ndujV/+9vfmDRpUtG8lJSUovc33XQTp556Kl27duWuu+6iTZs2QdcfNGgQrVq14rTTTqNTp0506tSJgd69Aj///DO1atUq87iHg8RDzcrPO/JiP0gTsqSaidEOwYRZvVoJldYfSERq4PKqPJ/PRgIpwIeBWuYOM/1uwFLgK9x9gwD34N0rqKpPicg44FrcSJ97gVtVdVmwdFNTUzXQTeWLvRE4w8033fFp4ytlG9VZWpr7u3hxNKMw4SQin6tqarTjiDWpndpo+srA90eFS15eHjVq1GDLli00btw4Jh7JsHbt2mKtLyb8pkyZQt26dWP6WX2RNmXKFI4++uiiQXt8BfpOViTfsoFcjDGx7iXgXeBpABG5F7gfWAVcIyLjVHV6eRNX1Y8o4yYWVZ2Ke2SEqabmzIl2BMZUDbt27eL555+nZ8+eRS0kpnq49tpreeWVV6IdRkypX78+w4YNi8i2rHunMSbWpQL/9pm+ARjj1XT9Dij5MCJjwuykk9zLGFN+v/zyC9OnT6ddu3ZFg1+Y6iMpKSliBZx4MWrUqEp/Pl8hK/QZY2JdA1XdAiAiyUA94GVv3nygeZTiMtXISy+5lzGm/JYvX06PHj0477zzDutRA8aYirPuncaYWLdbROp4o2emAqtVtXBsZ8HyMRMBTz7p/vqMXWBMFRX+wlhmZiaNGjViwIABVtgzJkrsYskYE+uWAhNF5J+4xzO84zOvLVByiLJqLpTHNthgL8aYSEhPT2fJkiUMGTLECnzGRJF17zTGxLo7gQuBr4GjAd/HKlwJfBSNoIwxxgT30UcfsWzZMkaNGsUJJ5wQ7XDCZtcueOABOPZYSEhwfx94wH1uTKyylj5jTExT1e+AZBFpqKq/+s2eDByIQlhxr6zWQGsJNMaUV0FBASJC8+bNOf3008PyDLVYsWsXdO4M69fDPu9Gg19+gcmTYd48+OQTqFOnfGknJiZy2mmnFT3SYsSIEdx8880kJBx+G839999Pjx49Aj6EHOCpp56idu3aDB8+vHzBerKyskhOTqZt27YcOHCAHj16MG3atFJjDmW7GRkZbNmyhf79+1coNlOcFfqMMXEhQIEPVc2JRizGGGMCO3DgAK+88grt27cv9kDrquKRR4oX+Art2+c+f+QRePDB8qVdq1YtMjIyANi6dStDhw4lNzeXB8uR4IQJE4LOHzt2bLliDKRVq1ZkZGSQn59Pr169mD9/Pr/97W/Lvd2MjAzS09Ot0BdmVugzxhhTgrUEFvfqq9GOwJjYt3v3bl544QUaN25Mx44dox1OpZg2rWSBr9C+fW7Qp/IW+nw1btyYp59+mrPOOovx48dTUFDAXXfdxeLFi9m/fz/XX38911xzDQCTJ09mzpw5JCQk0K9fPyZNmsTIkSMZMGAAgwYN4q677uKNN96gRo0a9OnTh0cffZTx48dTp04dbrvtNjIyMhg7dix79uyhVatWzJgxgwYNGpCWlsY555zDBx98QE5ODtOnT6d79+6lxlyjRg26dOnCunXr2LhxI6NHj2bbtm0ce+yxPPvsszRr1qzYdgOlf84553D//fezd+9ePvroI+6++24G2whaYWGFPmOMqQLSZi4OOn/xyLSIxFFVHXNMtCMwJkIqMNjKsmXLaN26NWlpaVV20Jbs7IrNPxwtW7akoKCArVu3smDBAurVq8dnn33G/v376dq1K3369OGbb75h/vz5fPrpp9SuXZtffy3eKebXX3/l9ddf55tvvkFEyMkp2UFm+PDhPPHEE5x33nncf//9PPjggzz22GMA5Ofns2LFCt5++20efPBBFi5cWGq8e/bsYdGiRUyYMIFx48YxfPhwRowYwYwZM7jxxhuZP39+iXUCpT9hwgTS09OZOnVqBY+g8WWFPmOMMYetuo0QOnOm+ztyZDSjMCY2/fDDD9SsWZMLLrigyhb2CjVq5O7hCzY/nFQVgPfee49Vq1bxqtftIDc3l2+//ZaFCxcyatQoateuDUDDhg2LrX/00UeTlJTEmDFj+M1vfsOAAQOKzc/NzSUnJ4fzzjsPgBEjRnD55ZcXzS/spnnmmWeSlZUVMMb169eTkpKCiHDxxRfTr18/hg0bxmuvvQbAsGHDuOOOOwKuG0r6Jjys0GeMMSYq4qkLqRX6jAksMzOTBQsWcOmll9K4ceNoh1PprrvODdoSqItnUhJce234trVhwwYSExNp3LgxqsoTTzxB3759iy3zzjvvBC1o16hRgxUrVrBo0SLmzp3L1KlTef/990OO4cgjjwTcIDP5+fkBlym8py+Y0mIMJX0THlboM8YYUylCaQ00xsSvlStXsnDhQoYMGULTpk2jHU5E3H67G6XTfzCXpCRo1crND4dt27YxduxYxo0bh4jQt29fnnzySXr16kXNmjXJzMzkxBNPpE+fPkyYMIGhQ4cWde/0be3btWsXe/bsoX///nTu3JnWrVsX2069evVo0KABS5cupXv37syZM6eo1a8iunTpwty5cxk2bBjPP/883bp1C3ndunXrsnPnzgrHYIqzQp8xxpiYFI5CY1mtheHophqJFstIFKAjcaxM1VDY5bBRo0aMHDmSRuHu0xjD6tRxj2V45BE3aEt2tuvSee21rsBX3sc1AOzdu5eUlJSiRzYMGzaMW2+9FYAxY8aQlZXFGWecgapy7LHHMn/+fC688EIyMjJITU3liCOOoH///jz88MNFae7cuZOLL76Yffv2oapMmTKlxHZnzZpVNJBLy5YtefbZZ8u/E57HH3+c0aNH88gjjxQN5BKqnj17MmnSJFJSUmwglzCSwhM3lv28Iy/2gzQhS6qZGO0QTJjVq5VQtW/iKIfU1FRNT08v8Xm0BlSprgO5hKsgk5bm3i9eXL40qot4KvSJyOeqmhrtOGJNako7Tc/4ptT5BQUFvPXWWzRq1IguXbpEMLLKtXbtWpKTk6MdhjFFAn0nK5JvWUufMcaYKissrYWLx5OVM9J7P7PC6VVl8XSfpjl8Bw4cYN68eRw8eJA+ffpEOxxjzGGwQp8xxlQDwR7pUF1bAQ/HlZOej3YIxkRI6R03VqxYQa1atRg4cCCJidZrx5h4YoU+Y4wxpgw1k/KiHYIxUbN9+3b2799Ply5dEJEq+1gGVa2y+2biS2XcfmeFPmOMqebswe5l+2z+WQCcdclnUY7EmMjasmULL774Ir169eK4446LdjiVJikpiezsbBo1amQFPxNVqkp2djZJSUlhTdcKfcYYY0wZ1ixuD1ihr6Lsnr/4sn79el577TUGDBhQ5Qc5adq0KZs3b2bbtm3RDsUYkpKSwv4YFCv0GWOMMcaYYlSV2rVrM3jwYJo1axbtcCpdzZo1adGiRbTDMKbSWKHPGFPticiFwN+BROAZVZ3kN1+8+f2BPcBIVf0i4oFGSVndP0tj3UKNqTyVmW99+OGH5OXlcf7554c5amNMtFihzxhTrYlIIvAPoDewGfhMRN5Q1a99FusHnOK9zgGe9P6aIMpbWAQrMBoTTGXmW7k79/L1119z5ZVXhj9wY0zUWKHPGFPdnQ2sU9UNACIyF7gY8L14uhiYrW44rU9EpL6IHK+qP0Y+3OqhIgXGyjD/p0uiHUK1EMpzFe2+P6AS8638gwWMGjWKI488srJiN8ZEQVwU+pocXbNaDKMkIler6tPRjsOEj/1P48KJwPc+05spWRseaJkTgWIXTyJyNXC1N7lfRFaHN9SIOQb4JdpBlEMlxn06ACt7Vk7q2DEP2YM8GK6k2oYroSgIW74FJfOupKSkeMy74vUcgviNPV7jhviNvdz5VlwU+qqRqwErIFQt9j+NfYEqlfwfkBPKMngF/KcBRCRdVVMrHl7kxWvs8Ro3xG/s8Ro3uNijHUMFhC3fgqqRd8Vr3BC/scdr3BC/sVck30oIZyDGGBOHNgMn+Uw3BbaUYxljjIkUy7eMMYfFCn3GmOruM+AUEWkhIkcAVwBv+C3zBjBcnM5Art3PZ4yJIsu3jDGHxbp3xhbrBlj12P80xqlqvoiMA97FDX0+Q1XXiMhYb/5TwNu4Yc/X4YY+HxVC0vH8v4/X2OM1bojf2OM1bojj2Csx34L4PS7xGjfEb+zxGjfEb+zljlvcoE7GGGOMMcYYY6oi695pjDHGGGOMMVWYFfqMMcYYY4wxpgqzQl+MEJELReR/IrJORO6KdjymYkRkhohsjePntJkQlXXueoMoPO7NXyUiZ0QjzkBCiP1KL+ZVIrJMRDpFI05/oeaXInKWiBwUkUGRjC+YUGIXkTQRyRCRNSKyJNIxBhLCd6WeiLwpIiu9uEO9f6xSlZUXx/L5WZks34o8y7ciz/ItP6pqryi/cDdhrwdaAkcAK4FTox2XvSr0P+0BnAGsjnYs9qrU/3OZ5y5uIIX/4J6Z1Rn4NNpxH0bsXYAG3vt+sRB7qPmlt9z7uMEsBkU77sM45vWBr4Fm3nTjOIn7HuAv3vtjgV+BI2Ig9qB5cayenzHw/4zJ42L5VmzGbvlW2GOvlHzLWvpiw9nAOlXdoKoHgLnAxVGOyVSAqn6IyzxM1RbKuXsxMFudT4D6InJ8pAMNoMzYVXWZqm73Jj/BPecr2kLNL28A5gFbIxlcGUKJfSjwmqpuAlDVWIg/lLgVqCsiAtTB5X/5kQ2zpBDy4lg9PyuT5VuRZ/lW5Fm+5ccKfbHhROB7n+nN3mfGmNgWyrkbq+f34cZ1Fa5mMdrKjFtETgQuBZ6KYFyhCOWYtwEaiMhiEflcRIZHLLrShRL3VCAZ9/Dvr4CbVLUgMuFVSKyen5XJ8q3Is3wr8izf8mPP6YsNEuAze5aGMbEvlHM3Vs/vkOMSkZ64i6dulRpRaEKJ+zHgTlU96CpwY0YosdcAzgTOB2oBy0XkE1XNrOzggggl7r5ABtALaAX8V0SWquqOyg6ugmL1/KxMlm9FnuVbkWf5lh8r9MWGzcBJPtNNcbUOxpjYFsq5G6vnd0hxiUhH4Bmgn6pmRyi2YEKJOxWY6104HQP0F5F8VZ0fmRBLFer35RdV3Q3sFpEPgU5ANC+eQol7FDBJ3Q0n60TkO6AdsCIyIZZbrJ6flcnyrcizfCvyLN/yY907Y8NnwCki0kJEjgCuAN6IckzGmLKFcu6+AQz3RtvqDOSq6o+RDjSAMmMXkWbAa8CwKNfY+iozblVtoarNVbU58CpwXQxcOEFo35cFQHcRqSEitYFzgLURjtNfKHFvwtXyIyJNgLbAhohGWT6xen5WJsu3Is/yrcizfMuPtfTFAFXNF5FxwLu40YZmqOqaKIdlKkBEXgTSgGNEZDPwgKpOj25UJtxKO3dFZKw3/yncKGz9gXXAHlzNYtSFGPv9QCNgmlf7nK+qqdGK2YsrlLhjUiixq+paEXkHWAUUAM+oalQf/RLiMZ8IzBSRr3Bdj+5U1V+iFrQnUF4M1ITYPj8rk+VbkWf5VuRZvhUgXdeiaYwxxhhjjDGmKrLuncYYY4wxxhhThVmhzxhjjDHGGGOqMCv0GWOMMcYYY0wVZoU+Y4wxxhhjjKnCrNBnjDHGGGOMMVWYFfoMItJNRNRn+ikRmRrhGBaKyPhKSjtNRPIrI21j4lEo53g08oGKqOh5LiLNRURFpGmQZf4jInf4TKuIdPPedxeRnPJuP8g2k0TkWxFpG+60y9huU2//mnvT94jImxGO4RkRmem9uzyl+QAAEApJREFUP9I7Du0iGYMxhURksYjcG+04DoeIrBGRwRVdxlQNVuiLcV4ms19EdolIroh8KSKXVeY2VXWsqo47jPgqLRMUkSNEZKuIjA4wr46I7BCRQZW1fWOiqbLOf/9zXESyROR3wZYJN2+b+7x92y4iH4tIWmVtLxxUtZ+qTi5l3lJVrV84LSLjRWRhGDZ7E7BcVf8XhrTKTVUfVtWBoSwrIjNF5Jkwb38/8CjwSDjTNdWPX75a+Arr97UcMamI7PFi+UVE3hORThVNV1Xbq+pL3jYCVmz5LhNuPtvc7e3bVhF5XURaHEYa4cpLqz0r9MWHiapaB/ew0ReBl0Skjf9CIlIz4pFVMlU9AMwEfh9g9hDcQykXRDImYyIspPM/To3x9u0E4HPgTRGp579QVczbQiEiicA44F8VSUNEqspv/YtALxFpHe1ATNybqKp1fF5joh0Q0MfLD1sBuUBEW9YrWVtv39oD9YFnoxxPtVRVfgiqBVXNB6YBicBphd2ZRGSYiGwAfgUQkWYi8qqI/Oi9nhaRuoXpiMgpXk3XThFZCaT6bse/llZEjhWR6SKyyWtZ+1xE2npdv7oD93k1OP/zWef3IrLap3Wij888EZG7RWSziPwqIlMACbLrTwPniMhpfp9fDcwAaorIayLykxffFyLSu7TEAtVC+7d0iOuq9ZEX33oR+YOIiDevgYi8IiLZ3v6tFpHuQeI3psL8z38AEblWRP7nfQ8/8f0eisjp3nc41/seLxORBt68onNAXJe9ZsAz3nn8XoBlHhWR133jEZGeXh5ylDfdQUTe9WqpN4nIn0MtrKnqXtx5XgdoLSIjRWSdiNwuIpuBDG8b54nIp94+fSMi1/inJSIjRGSjt88zRaSOz7yHRWSDt5/rReTmAOFcKCKZIpIjIgtEpLHP+qX2bBCf7qXiukrdA6TJoZaEViLyg4hc6rfebBGZXsqhSQUaAMt9li88Nnd6+ftWEflr4bGWQzXrV4nI17iKscYi0sjLx78XkW0i8rKINPFJ9zgRecM7tpnAhX5xFqttF9fT4lHveO4U10Wsm7jur1cCI3z2PdFb5xJxvx85IrJWRK7028Zo7/+yQ0TmAEm+81V1B/AZcFEpx8uYchORK0Rkpff9+1FE/lmYvwVY9ghx11ZbveUzxafXkQS5hiiLquYCs4CTvPO2toj83Tt3fxGR+SLSzC/utd55+LN4XaK9eb7XNiu9v//zzsv7/JcRkXQRuclvXx8Ukfd9poOex2Xs2zbgVXyuO0Wkk4gs8fZtu7hu9K28eYHy0pbevHIf4+rKCn1xRESOAK4H8jh08iYC/YDTgSYikgS8D3wNtAROBZoCf/fSqIGrPVoDNAYGAWODbDMB15JWHzjL+zsK2Ol1/VrKoRqztt46VwN34n74GwB/BF6TQ7WzvwNuAS4GjgN+AXqUFoOqrgM+wKe1T0RSgDOBZ3Df49eAUzjUGjJPRI4tLc1gRKQ98DauG9GxwG9wte3DvEVuB2oDJ3vH47fA5vJsy5hQ+Z//IjIEmAgMx33v/wW8IyIne6v8A3gPaAg0AW4FDvin63XZ24TX6qaqffyXwVWu/MbvnBoJvKyqu8UVjJbgzsMTgHOB3sDdIe7bUcA1uNrtTO/j5l5apwBniesO9A7wlLe/I4E/i8jlPkklAgOBjkAy0Ab4q8/8r4FuQF1cfvJnEenrF85wXH7UDCgAngtlH3x5XaUeBhb7tCSsB6YDRS0K4lo1B1F6S94ZQKZX4Pd1shdfS9yxHgjc5rfMUKAXbl+3AfMBBTp46+8EXvBZ/nngoJduD9zxDWY6cA5wPnA0cAnwk9f99Xlgls++HxRXETcduBn3nRwBTBWRHt6x6I77zo715v8XCHSf0VfecTEm3HJx5019XIV2d6C021dG4q6JklX1aNx58DWEdA0RlLjKuZHAd6qaDUwBOnuvk3HXTG+Ka8WvDcwBrlfVurg8obRKpMLuom2983JigGVm4K7xCmMRXJ74rDcd9DwOYd+Ow53Xvt3VFRgPnIjL93fh5bul5KUbKnqMqy1VtVcMv4DFwF4gB9gKLAMGevPScCdLM5/lBwHr/dI4E9iPuyDq6r2v7TP/9+6rUDQ9E3jGe3827iKzXpD47vX7bDUw3O+zNwuXw/2YT/SZlwB8D4wPchz+D9eSmeRNPwm8G2T5X4D+PscpP9D++XyWBfzOez8VmOE3/w/AQu/9eOAT77gmRPs7Yq+q+yrj/H8P+JPf8suBu33WfQZoHiDdYueA7/c/yDKfArd47+vifpi7etO3Ae/7rX8ZsC7IvmUBu719+xlY5JPeSG+/j/RZ/h7gY780/lyYD3AoP2zlM/8CYF9p5ymuxnmy9765t/75PvNbe5+d4HNM7/WZr0A3n+375jPjC/MMn8+a4QreJ3rT1wJfBTlG9+Audnw/G0nJPHwMrnDoux89fOan4lr8fI9nI2+5priLLf9j19v7rLn//uAqDBVoX0rcxb473mf/Bu73++wJDv3W/AuY4zf/Y2Cm32d/At6O9rlpr/h9UTxfLXx1DrDcOGCF33qF1zEjgW9xBcMafusFvYYoJSbFVcTkAFuAN3BdIRO8WHv7LFvHy0fOxVVA7wGuAxoGSDeLQ9c2hXlD0yDLNMDlmad7071wheHa3nTQ8zjA9gu3mevtn+IqbtoGORYdvOWO8qaL8p6KHGN7qbX0xYk/qWp9VW2sql1U1befdwGuwFSoBdDMa3bPETea3CLcCXQc7gd+q6ru8VnnuyDbbu4tn3sY8bYA/uEXQ0/chQVeDFmFC6tqAbCxjDRfxxU+L/daBYYC/wQQkVoi8oTXzWiHt70GuNqf8mgBDPGL/wHgeG/+I7hjOgvYJiKzxKeblDFhVtr5fxKwwW/Z9d7n4GprE4CPROQ7EZnotfSX17McqgH+P+AHVf3Ym24BdPU7Z2bg8pxgrvH2rYmqnu+THsCP6gbvKFTW/hbyzUuygCOBYwBE5EYR+crrQpSDayHzzyeyArwvdUTPw6Gqm3CVXoXHcQzB79fbjmtF8+efh2cFiDHL530L3HH42ef/sx53cdfMZ13fY1fW7wIcapUNRQvgTr/vyEhcay74/S4EieFovFsZjKmAwny18PWJiPQWkaXiuj/vAP5C6dcRz+Eq1aYA2eJuMSnszVTWNURp+nmxnKCqF6nqGm/7Sfjkfaq6C1cJeJKXD/THdcde73W7HFquI+LS3o7rFVCYR40C5vrkN2Wdx6Vpr64l8ixcC2HLwhniur6/Jq77+w5cZQ94+XYpynuMqzUr9MU/Va+Kw7MRV+Nb3++VpKo/AD/g7u+o7bNOsFGUsrzlA114gCt0+tsIjPbbfh1Vvdab/wOHLhoKuw+cHCAd353M49CALlfgarbe8GbfCpyH615RT90Ietsp/T7BXUBRP33vQrixz/yNuBok3/iPVtX2Xiy7VfWPqtoBVxN3IjainIm87yl57rb0PkdVv1PV0araFHcP1BhcN51AAp3H/uYCp4jIGbgfed8b8Tfialh9z5l66m7cLy//mILurw/fvKQ5rlXsFxHpiruIuwY4xssn3qRkPtE8wPvydN8u7Zj+ExgtIqfjut/PCZLGl0Ab8e6J8+GfhzcPEKPv9jfiWlUb+v2PaqnqMlyeDMWPXVm/C+C63gZS2u/CeL/t11XV/t78Yr8LQWLogDsuxoSN131+Pi6fa6auy+adlHIdoar5qvoXVU3FnTd7cBVdUMY1xGHahsvDis4FcfcpN+ZQXr9YVS/CFZIeAp4rvCfOTyj5PLi8faiIHIO7fcU/rw92Hgelqum4LrP/8snDnsK1Anb0jnvXwl0NEnc4j3G1YYW+quffuIFN7hGRuuKcKIcGD/gEd7JM8lrIWuHurytNOm5UvWdEpLGIJIjIaSJSWJvyE64LlK8pwHgRSfG2X0vcDf6Fz1eaA1wtImeIG3zgLspuEQA30ENX3D2CM/TQfS5H4zLFbOAIEbkf1yc/2D6dLyItRORIXHch3wEnpgFXiMhAEakpIjVE5FQROQ/A+zzZuxDbhastt+cAmkibCVwjImd739GRQAruntbCAU0Ka19zcN/R0r6nP1H6BTwAqpqDa3F/CHdvyWyf2bOBVHEDcSR5+URLEbkwUFrl9CJwpogM9/b3bFwBzv/+lT+LyNHi7jMcj+syWIDLJw7iLqJURH6Dux/a330i0sSr6PoLsEhVt5Qj3p9wvS6O8Pv8LeAIL+55Xs16aT7D/e/O9fs8gUN5eEtc99pZQdJJxw2G83cRaQRFA3RdAaCqm3Fd1yZ7x64JcF9pianqVlzX2GniBo4REWnt09LxE9BSio8a+hhws7jBFxLFDYRxpogUDugwGxgkIud7/9/f4W4vKCJuQLKzOVThZ0y4HIFrUduuqntF5FRc986ARKSX9/2tiet+uZtD+WvQa4jD4eVds4GJInKCV1D6K/ANsMLLqy4TkXqqehCXX4DL6/xtwxWggub1uN4Ie73tblTVT3zmlXUeh2I27njd6E0f7U3neAXNCX7LB8pLw3aMqxMr9FUxXhP8+bga5G9w/agX4S4G8QpKF+Fu6N2KG3jh6SDpFXjL78VdNOTgan0KRwOdgrvYyxGRNd46/wIme8ttxw0ScR+HClazcX3A38Tdy9MY+DCEfVuPG6SmOa5bRaG/cagf/HpcjVtWkKSex100fOEtv4lDNd2o6mpgAO5G5R9xx2kmh7p5tPJi3+FtZy+u4GpMxKjqC8CDuG5G2bh7Ovqrapa3SC/gcxHZhbvX7wXcdz+Qh4DfiTdyWpDNPosrKL3rWxBS1Z9wXbgvwZ0T23EFxJYB0igXVf0O141pHG5/5+DuLXnZZ7GDuELVV7iBAjbgegIAvOutswJ3z+8gL0Z/z+EGqPoedyH4uwDLhOIVL42fvPyxhbcfB3EFvtMp41EM3rJT8Rn8xbMRl2d9h7vX8h1cnltaOgW4/00C7jux01svzWexobguoN/j9n82wY3G/SYswdXSL+BQ5d0zuN4U2d6+J6rqe7gRlx/BHf8fcb8fdbwYPwRu8Nb9Fdddzf/ZYUOAD1T12zJiM+aweF0mr8VVfOzCDSr0QpBVmuDyk+247/LJuEqoUK4hDtctuIqbz3DXK8cDF3n5QwJugK8s77z+BzDC53fAdx/34q7FXvTOyz8G2phPQbMfh1ovC+cFPY9D4cU9EddNtIG3f91x11RLcY0XvkrkpZVwjKsFKd4z0BhjjDGVyWuVvVu9EY/LWLYWsAoYoKr/89a9V1Wr1bPqvF4Zq3EXu2ujHY8xxsSbitzUb4wxxpjD4HVRvAl4PJTlvdr5srpjVXnqBvWp9sfBGGPKy7p3GmOMMREg7mHwP+O6Z5bard4YY4wJN+veaYwxxhhjjDFVmLX0GWOMMcYYY0wVZoU+Y4wxxhhjjKnCrNBnjDHGGGOMMVWYFfqMMcYYY4wxpgqzQp8xxhhjjDHGVGH/DyaG/zhBUZNUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1080x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Precision: 0.916 | Recall: 0.328 | F1 Score: 0.482 | AUC: 0.908\n"
     ]
    }
   ],
   "source": [
    "### PLOT AND STORE RESULTS ###\n",
    "\n",
    "results['Param Tuning + RFE'] = binary_performances(y_test, model.predict_proba(X_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "12 trials detected for ('n_estimators', 'learning_rate', 'num_leaves')\n",
      "\n",
      "trial: 0001 ### iterations: 00046 ### eval_score: 0.91769\n",
      "trial: 0002 ### iterations: 00026 ### eval_score: 0.91573\n",
      "trial: 0003 ### iterations: 00061 ### eval_score: 0.93528\n",
      "trial: 0004 ### iterations: 00035 ### eval_score: 0.91223\n",
      "trial: 0005 ### iterations: 00062 ### eval_score: 0.91467\n",
      "trial: 0006 ### iterations: 00030 ### eval_score: 0.90345\n",
      "trial: 0007 ### iterations: 00085 ### eval_score: 0.91516\n",
      "trial: 0008 ### iterations: 00024 ### eval_score: 0.90362\n",
      "trial: 0009 ### iterations: 00064 ### eval_score: 0.91703\n",
      "trial: 0010 ### iterations: 00090 ### eval_score: 0.94616\n",
      "trial: 0011 ### iterations: 00051 ### eval_score: 0.90968\n",
      "trial: 0012 ### iterations: 00010 ### eval_score: 0.89363\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "BoostRFE(estimator=LGBMClassifier(random_state=0), greater_is_better=True,\n",
       "         importance_type='shap_importances', min_features_to_select=10,\n",
       "         param_grid={'learning_rate': [0.3, 0.2, 0.1], 'n_estimators': 200,\n",
       "                     'num_leaves': [20, 25, 30, 35]},\n",
       "         step=3, train_importance=False)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### HYPERPARAM TUNING WITH GRID-SEARCH + RECURSIVE FEATURE ELIMINATION (RFE) WITH SHAP ###\n",
    "\n",
    "model = BoostRFE(lgbm, param_grid=param_grid, min_features_to_select=10, step=3, greater_is_better=True,\n",
    "                 importance_type='shap_importances', train_importance=False)\n",
    "model.fit(X_train, y_train, eval_set=[(X_valid, y_valid)], eval_metric=AUC, early_stopping_rounds=3, verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Precision: 0.875 | Recall: 0.574 | F1 Score: 0.693 | AUC: 0.946\n"
     ]
    }
   ],
   "source": [
    "### PLOT AND STORE RESULTS ###\n",
    "\n",
    "results['Param Tuning + RFE w/ SHAP'] = binary_performances(y_test, model.predict_proba(X_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### PLOT AND COMPARE RESULTS ###\n",
    "\n",
    "plt.figure(figsize=(12,5))\n",
    "\n",
    "plt.bar(np.arange(4)-0.05, results['Param Tuning'].values(), \n",
    "        alpha=0.5, width=0.1, label='Param Tuning')\n",
    "plt.bar(np.arange(4)+0.05, results['Param Tuning + RFE'].values(), \n",
    "        alpha=0.5, width=0.1, label='Param Tuning + RFE')\n",
    "plt.bar(np.arange(4)+0.15, results['Param Tuning + RFE w/ SHAP'].values(), \n",
    "        alpha=0.5, width=0.1, label='Param Tuning + RFE w/ SHAP')\n",
    "\n",
    "plt.xticks(range(4), results['Param Tuning'].keys())\n",
    "plt.ylabel('scores'); plt.legend()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:prova]",
   "language": "python",
   "name": "conda-env-prova-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
